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Federated Learning Resources

Stars Awesome License

Table of Contents

We use another project to automatically track updates to FL papers, click on FL-paper-update-tracker if you need it.

More items will be added to the repository. Please feel free to suggest other key resources by opening an issue report, submitting a pull request, or dropping me an email @ ([email protected]). If you want to communicate with more friends in the field of federated learning, please join the QQ group [联邦学习交流群], the group number is 833638275. Enjoy reading!

Repository Update Notice

2024/09/30

Dear Users, We would like to inform you of a few changes that will affect this open source repository. The owner and principal contributor @youngfish42 has successfully completed his doctoral studies 🎓 as of September 30, 2024, and has since shifted his research focus. This change in circumstances will impact the frequency and extent of updates to the repository's paper list.

Instead of the previous regular updates, we anticipate that the paper list will now be updated on a monthly or quarterly basis. Furthermore, the depth of these updates will be reduced. For instance, updates related to the author's institution and open source code will no longer be actively maintained.

We understand that this might affect the value you derive from this repository. Therefore, we humbly invite more contributors to participate in updating the content. This collaborative effort will ensure that the repository remains a valuable resource for everyone.

We appreciate your understanding and look forward to your continued support and contributions.

Best Regards,

白小鱼 (youngfish)

papers

categories

  • Artificial Intelligence (IJCAI, AAAI, AISTATS, ALT, AI)

  • Machine Learning (NeurIPS, ICML, ICLR, COLT, UAI, Machine Learning, JMLR, TPAMI)

  • Data Mining (KDD, WSDM)

  • Secure (S&P, CCS, USENIX Security, NDSS)

  • Computer Vision (ICCV, CVPR, ECCV, MM, IJCV)

  • Natural Language Processing (ACL, EMNLP, NAACL, COLING)

  • Information Retrieval (SIGIR)

  • Database (SIGMOD, ICDE, VLDB)

  • Network (SIGCOMM, INFOCOM, MOBICOM, NSDI, WWW)

  • System (OSDI, SOSP, ISCA, MLSys, EuroSys, TPDS, DAC, TOCS, TOS, TCAD, TC)

  • Others (ICSE, FOCS, STOC)

Events
Venue 2024-2020 before 2020
IJCAI 24, 23, 22, 21, 20 19
AAAI 24, 23, 22, 21, 20 -
AISTATS 24, 23, 22, 21, 20 -
ALT 22 -
AI (J) 23 -
NeurIPS 24, 23, 22, 21, 20 18, 17
ICML 24, 23, 22, 21, 20 19
ICLR 24, 23, 22, 21, 20 -
COLT 23 -
UAI 23, 22, 21 -
Machine Learning (J) 24, 23, 22 -
JMLR (J) 24, 23, 22 -
TPAMI (J) 23, 22 -
KDD 24, 23, 22, 21, 20
WSDM 24, 23, 22, 21 19
S&P 24, 23, 22 19
CCS 23, 22, 21, 19 17
USENIX Security 23, 22, 20 -
NDSS 24, 23, 22, 21 -
CVPR 24, 23, 22, 21 -
ICCV 23,21 -
ECCV 24, 22, 20 -
MM 24, 23, 22, 21, 20 -
IJCV (J) 24 -
ACL 23, 22, 21 19
NAACL 24, 22, 21 -
EMNLP 24, 23, 22, 21, 20 -
COLING 20 -
SIGIR 24, 23, 22, 21, 20 -
SIGMOD 22, 21 -
ICDE 24, 23, 22, 21 -
VLDB 23, 22, 21, 21, 20 -
SIGCOMM - -
INFOCOM 24, 23, 22, 21, 20 19, 18
MobiCom 24, 23, 22, 21, 20
NSDI 23(1, 2) -
WWW 24, 23, 22, 21
OSDI 21 -
SOSP 21 -
ISCA 24 -
MLSys 24, 23, 22, 20 19
EuroSys 24, 23, 22, 21, 20
TPDS (J) 24, 23, 22, 21, 20 -
DAC 24, 22, 21 -
TOCS - -
TOS - -
TCAD 24, 23, 22, 21 -
TC 24, 23, 22, 21 -
ICSE 23, 21 -
FOCS - -
STOC - -

keywords

Statistics: 🔥 code is available & stars >= 100 | ⭐ citation >= 50 | 🎓 Top-tier venue

kg.: Knowledge Graph | data.: dataset  |   surv.: survey

fl in top-tier journal

Papers of federated learning in Nature(and its sub-journals), Cell, Science(and Science Advances) and PANS refers to WOS search engine.

fl in top-tier journal
Title Affiliation Venue Year Materials
MatSwarm: trusted swarm transfer learning driven materials computation for secure big data sharing USTB; NTU Nat. Commun. 2024 [PUB] [CODE]
Introducing edge intelligence to smart meters via federated split learning HKU Nat. Commun. 2024 [PUB] [新闻]
An international study presenting a federated learning AI platform for pediatric brain tumors Stanford University Nat. Commun. 2024 [PUB] [CODE]
PPML-Omics: A privacy-preserving federated machine learning method protects patients’ privacy in omic data KAUST Science Advances 2024 [PUB] [CODE]
Federated learning is not a cure-all for data ethics TUM; UvA Nat. Mach. Intell.(Comment) 2024 [PUB]
Robustly federated learning model for identifying high-risk patients with postoperative gastric cancer recurrence Jiangmen Central Hospital; Guilin University of Aerospace Technology; Guilin University of Electronic Technology; Nat. Commun. 2024 [PUB] [CODE]
Selective knowledge sharing for privacy-preserving federated distillation without a good teacher HKUST Nat. Commun. 2024 [PUB] [PDF] [CODE]
A federated learning system for precision oncology in Europe: DigiONE IQVIA Cancer Research BV Nat. Med. (Comment) 2024 [PUB]
Multi-client distributed blind quantum computation with the Qline architecture Sapienza Università di Roma Nat. Commun. 2023 [PUB] [PDF]
Device-independent quantum randomness–enhanced zero-knowledge proof USTC PNAS 2023 [PUB] [PDF] [新闻]
Collaborative and privacy-preserving retired battery sorting for profitable direct recycling via federated machine learning Tsinghua University Nat. Commun. 2023 [PUB]
Advocating for neurodata privacy and neurotechnology regulation Columbia University Nat. Protoc. (Perspective) 2023 [PUB]
Federated benchmarking of medical artificial intelligence with MedPerf IHU Strasbourg; University of Strasbourg; Dana-Farber Cancer Institute; Weill Cornell Medicine; Harvard T.H. Chan School of Public Health; MIT; Intel Nat. Mach. Intell. 2023 [PUB] [PDF] [CODE]
Algorithmic fairness in artificial intelligence for medicine and healthcare Harvard Medical School; Broad Institute of Harvard and Massachusetts Institute of Technology; Dana-Farber Cancer Institute Nat. Biomed. Eng. (Perspective) 2023 [PUB] [PDF]
Differentially private knowledge transfer for federated learning THU Nat. Commun. 2023 [PUB] [CODE]
Decentralized federated learning through proxy model sharing Layer 6 AI; University of Waterloo; Vector Institute Nat. Commun. 2023 [PUB] [PDF] [CODE]
Federated machine learning in data-protection-compliant research University of Hamburg Nat. Mach. Intell.(Comment) 2023 [PUB]
Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer Owkin Nat. Med. 2023 [PUB] [CODE]
Federated learning enables big data for rare cancer boundary detection University of Pennsylvania Nat. Commun. 2022 [PUB] [PDF] [CODE]
Federated learning and Indigenous genomic data sovereignty Hugging Face Nat. Mach. Intell. (Comment) 2022 [PUB]
Federated disentangled representation learning for unsupervised brain anomaly detection TUM Nat. Mach. Intell. 2022 [PUB] [PDF] [CODE]
Shifting machine learning for healthcare from development to deployment and from models to data Stanford University; Greenstone Biosciences Nat. Biomed. Eng. (Review Article) 2022 [PUB]
A federated graph neural network framework for privacy-preserving personalization THU Nat. Commun. 2022 [PUB] [CODE] [解读]
Communication-efficient federated learning via knowledge distillation THU Nat. Commun. 2022 [PUB] [PDF] [CODE]
Lead federated neuromorphic learning for wireless edge artificial intelligence XMU; NTU Nat. Commun. 2022 [PUB] [CODE] [解读]
A novel decentralized federated learning approach to train on globally distributed, poor quality, and protected private medical data University of Wollongong Sci. Rep. 2022 [PUB]
Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence HUST Nat. Mach. Intell. 2021 [PUB] [PDF] [CODE]
Federated learning for predicting clinical outcomes in patients with COVID-19 MGH radiology and Harvard Medical School Nat. Med. 2021 [PUB] [CODE]
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning Imperial College London; TUM; OpenMined Nat. Mach. Intell.(Perspective) 2021 [PUB]
Swarm Learning for decentralized and confidential clinical machine learning ⭐ DZNE; University of Bonn; Nature 🎓 2021 [PUB] [CODE] [SOFTWARE] [解读]
End-to-end privacy preserving deep learning on multi-institutional medical imaging TUM; Imperial College London; OpenMined Nat. Mach. Intell. 2021 [PUB] [CODE] [解读]
Communication-efficient federated learning CUHK; Princeton University PANS. 2021 [PUB] [CODE]
Breaking medical data sharing boundaries by using synthesized radiographs RWTH Aachen University Science. Advances. 2020 [PUB] [CODE]
Secure, privacy-preserving and federated machine learning in medical imaging ⭐ TUM; Imperial College London; OpenMined Nat. Mach. Intell.(Perspective) 2020 [PUB]

fl in top ai conference and journal

Federated Learning papers accepted by top AI(Artificial Intelligence) conference and journal, Including IJCAI(International Joint Conference on Artificial Intelligence), AAAI(AAAI Conference on Artificial Intelligence), AISTATS(Artificial Intelligence and Statistics), ALT(International Conference on Algorithmic Learning Theory), AI(Artificial Intelligence).

fl in top ai conference and journal
Title Affiliation Venue Year Materials
Federated Multi-View Clustering via Tensor Factorization IJCAI 2024 [PUB]
Efficient Federated Multi-View Clustering with Integrated Matrix Factorization and K-Means IJCAI 2024 [PUB]
LG-FGAD: An Effective Federated Graph Anomaly Detection Framework IJCAI 2024 [PUB]
Federated Prompt Learning for Weather Foundation Models on Devices IJCAI 2024 [PUB]
Breaking Barriers of System Heterogeneity: Straggler-Tolerant Multimodal Federated Learning via Knowledge Distillation IJCAI 2024 [PUB]
Unlearning during Learning: An Efficient Federated Machine Unlearning Method IJCAI 2024 [PUB]
Practical Hybrid Gradient Compression for Federated Learning Systems IJCAI 2024 [PUB]
Sample Quality Heterogeneity-aware Federated Causal Discovery through Adaptive Variable Space Selection IJCAI 2024 [PUB] [CODE]
Feature Norm Regularized Federated Learning: Utilizing Data Disparities for Model Performance Gains IJCAI 2024 [PUB] [CODE]
Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks IJCAI 2024 [PUB]
FedConPE: Efficient Federated Conversational Bandits with Heterogeneous Clients IJCAI 2024 [PUB]
DarkFed: A Data-Free Backdoor Attack in Federated Learning IJCAI 2024 [PUB]
Scalable Federated Unlearning via Isolated and Coded Sharding IJCAI 2024 [PUB]
Enhancing Dual-Target Cross-Domain Recommendation with Federated Privacy-Preserving Learning IJCAI 2024 [PUB]
Label Leakage in Vertical Federated Learning: A Survey IJCAI 2024 [PUB]
The Rise of Federated Intelligence: From Federated Foundation Models Toward Collective Intelligence IJCAI 2024 [PUB]
LEAP: Optimization Hierarchical Federated Learning on Non-IID Data with Coalition Formation Game IJCAI 2024 [PUB]
EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in Federated Learning IJCAI 2024 [PUB]
Knowledge Distillation in Federated Learning: A Practical Guide IJCAI 2024 [PUB]
FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization IJCAI 2024 [PUB]
FedPFT: Federated Proxy Fine-Tuning of Foundation Models IJCAI 2024 [PUB] [CODE]
A Systematic Survey on Federated Semi-supervised Learning IJCAI 2024 [PUB]
Intelligent Agents for Auction-based Federated Learning: A Survey IJCAI 2024 [PUB]
A Bias-Free Revenue-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning IJCAI 2024 [PUB]
Dual Calibration-based Personalised Federated Learning IJCAI 2024 [PUB]
Stakeholder-oriented Decision Support for Auction-based Federated Learning IJCAI 2024 [PUB]
Redefining Contributions: Shapley-Driven Federated Learning IJCAI 2024 [PUB] [CODE]
A Survey on Efficient Federated Learning Methods for Foundation Model Training IJCAI 2024 [PUB]
From Optimization to Generalization: Fair Federated Learning against Quality Shift via Inter-Client Sharpness Matching IJCAI 2024 [PUB] [CODE]
FBLG: A Local Graph Based Approach for Handling Dual Skewed Non-IID Data in Federated Learning IJCAI 2024 [PUB]
FedFa: A Fully Asynchronous Training Paradigm for Federated Learning IJCAI 2024 [PUB]
FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning IJCAI 2024 [PUB]
FedES: Federated Early-Stopping for Hindering Memorizing Heterogeneous Label Noise IJCAI 2024 [PUB]
Personalized Federated Learning for Cross-City Traffic Prediction IJCAI 2024 [PUB]
Federated Adaptation for Foundation Model-based Recommendations IJCAI 2024 [PUB]
BADFSS: Backdoor Attacks on Federated Self-Supervised Learning IJCAI 2024 [PUB]
Estimating before Debiasing: A Bayesian Approach to Detaching Prior Bias in Federated Semi-Supervised Learning IJCAI 2024 [PUB] [CODE]
FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning IJCAI 2024 [PUB]
BOBA: Byzantine-Robust Federated Learning with Label Skewness UIUC AISTATS 2024 [PUB] [PDF] [CODE]
Federated Linear Contextual Bandits with Heterogeneous Clients University of Virginia AISTATS 2024 [PUB] [PDF] [CODE]
Federated Experiment Design under Distributed Differential Privacy Stanford University; Meta AISTATS 2024 [PUB] [PDF] [CODE]
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression Princeton University AISTATS 2024 [PUB] [PDF]
Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization INRIA AISTATS 2024 [PUB] [PDF]
SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization INRIA AISTATS 2024 [PUB] [PDF] [CODE]
Compression with Exact Error Distribution for Federated Learning École Polytechnique AISTATS 2024 [PUB] [PDF] [CODE]
Adaptive Federated Minimax Optimization with Lower Complexities NJU; MIIT Key Laboratory of Pattern Analysis and Machine Intelligence AISTATS 2024 [PUB] [PDF]
Adaptive Compression in Federated Learning via Side Information Stanford University; University of Padova AISTATS 2024 [PUB] [PDF] [CODE]
On-Demand Federated Learning for Arbitrary Target Class Distributions UNIST AISTATS 2024 [PUB] [CODE]
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning CMU AISTATS 2024 [PUB] [PDF] [CODE]
Queuing dynamics of asynchronous Federated Learning Huawei AISTATS 2024 [PUB] [PDF]
Personalized Federated X-armed Bandit Purdue University AISTATS 2024 [PUB] [PDF] [CODE]
Federated Learning For Heterogeneous Electronic Health Records Utilising Augmented Temporal Graph Attention Networks University of Oxford AISTATS 2024 [PUB] [CODE]
Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization University of Virginia AISTATS 2024 [PUB] [PDF]
Understanding Generalization of Federated Learning via Stability: Heterogeneity Matters Northwestern University AISTATS 2024 [PUB] [PDF] [CODE]
Provable Mutual Benefits from Federated Learning in Privacy-Sensitive Domains Sofia University AISTATS 2024 [PUB] [PDF] [CODE]
Analysis of Privacy Leakage in Federated Large Language Models University of Florida AISTATS 2024 [PUB] [PDF] [CODE]
Invariant Aggregator for Defending against Federated Backdoor Attacks UIUC AISTATS 2024 [PUB] [PDF] [CODE]
Communication-Efficient Federated Learning With Data and Client Heterogeneity ISTA AISTATS 2024 [PUB] [PDF] [CODE]
FedMut: Generalized Federated Learning via Stochastic Mutation NTU AAAI 2024 [PUB]
Federated Partial Label Learning with Local-Adaptive Augmentation and Regularization Carleton University AAAI 2024 [PUB] [PAGE]
No Prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation IIT AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Formal Logic Enabled Personalized Federated Learning through Property Inference Vanderbilt University AAAI 2024 [PUB] [PDF]
Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning against Attribute Inference Attacks Illinois Tech AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
FairTrade: Achieving Pareto-Optimal Trade-Offs between Balanced Accuracy and Fairness in Federated Learning Leibniz University AAAI 2024 [PUB] [PAGE]
Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators HKUST AAAI 2024 [PUB] [PAGE] [PDF]
Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity UT AAAI 2024 [PUB] [PAGE] [PDF]
On Disentanglement of Asymmetrical Knowledge Transfer for Modality-Task Agnostic Federated Learning University of Virginia AAAI 2024 [PUB]
FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning LMU Munich Siemens AG AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Watch Your Head: Assembling Projection Heads to Save the Reliability of Federated Models Xi'an Jiaotong University Shaanxi Joint Key Laboratory for Artificial Intelligence AAAI 2024 [PUB] [PAGE] [PDF]
FedGCR: Achieving Performance and Fairness for Federated Learning with Distinct Client Types via Group Customization and Reweighting NTU AAAI 2024 [PUB] [PAGE] [CODE]
Federated Modality-Specific Encoders and Multimodal Anchors for Personalized Brain Tumor Segmentation Xiamen University AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Exploiting Label Skews in Federated Learning with Model Concatenation NUS AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Complementary Knowledge Distillation for Robust and Privacy-Preserving Model Serving in Vertical Federated Learning SUST; HKUST AAAI 2024 [PUB] [PAGE]
Federated Learning via Input-Output Collaborative Distillation University at Buffalo; USA Harvard Medical School AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space University of Waterloo Vector Institute AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
FedCSL: A Scalable and Accurate Approach to Federated Causal Structure Learning HFUT AAAI 2024 [PUB] [PDF]
FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning Xi'an Jiaotong University; Leiden University AAAI 2024 [PUB] [PAGE] [PDF]
FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing NJU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Provably Convergent Federated Trilevel Learning TJU AAAI 2024 [PUB] [PDF]
Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts U-M AAAI 2024 [PUB] [PAGE]
General Commerce Intelligence: Glocally Federated NLP-Based Engine for Privacy-Preserving and Sustainable Personalized Services of Multi-Merchants Kyung Hee University; Harex InfoTech AAAI 2024 [PUB] [PAGE]
EMGAN: Early-Mix-GAN on Extracting Server-Side Model in Split Federated Learning Sony AI AAAI 2024 [PUB] [PAGE] [CODE]
FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy Labels SYSU; HKU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Point Transformer with Federated Learning for Predicting Breast Cancer HER2 Status from Hematoxylin and Eosin-Stained Whole Slide Images USTC; CAS AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
FedNS: A Fast Sketching Newton-Type Algorithm for Federated Learning CAS AAAI 2024 [PUB] [PDF] [CODE]
Federated X-armed Bandit Purdue University AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Algorithmic Foundation of Federated Learning with Sequential Data GMU AAAI 2024 [PUB]
UFDA: Universal Federated Domain Adaptation with Practical Assumptions XJTU; University of Sydney AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update Hithink RoyalFlush Information Network Co AAAI 2024 [PUB] [PAGE] [PDF]
Language-Guided Transformer for Federated Multi-Label Classification NTU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
FedCD: Federated Semi-Supervised Learning with Class Awareness Balance via Dual Teachers SZU AAAI 2024 [PUB] [PAGE] [CODE]
Beyond Traditional Threats: A Persistent Backdoor Attack on Federated Learning HEU AAAI 2024 [PUB] [PAGE] [CODE]
Federated Learning with Extremely Noisy Clients via Negative Distillation XMU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
FedST: Federated Style Transfer Learning for Non-IID Image Segmentation USTB AAAI 2024 [PUB] [PAGE] [学报] [CODE]
PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning USTC AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
A Privacy Preserving Federated Learning (PPFL) Based Cognitive Digital Twin (CDT) Framework for Smart Cities DCU AAAI 2024 [PUB]
A Primal-Dual Algorithm for Hybrid Federated Learning Northwestern University AAAI 2024 [PUB] [PAGE] [PDF]
FedLF: Layer-Wise Fair Federated Learning CUHK; Shenzhen Institute of Artificial Intelligence and Robotics for Society AAAI 2024 [PUB] [PAGE]
Towards Fair Graph Federated Learning via Incentive Mechanisms ZJU; FDU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Towards the Robustness of Differentially Private Federated Learning THU AAAI 2024 [PUB] [PAGE]
Resisting Backdoor Attacks in Federated Learning via Bidirectional Elections and Individual Perspective ZJU; HUAWEI AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Integer Is Enough: When Vertical Federated Learning Meets Rounding ZJU; Ant Group AAAI 2024 [PUB] [PAGE]
CLIP-Guided Federated Learning on Heterogeneity and Long-Tailed Data XMU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning FDU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Multi-Dimensional Fair Federated Learning SDU AAAI 2024 [PUB] [PAGE] [PDF]
HiFi-Gas: Hierarchical Federated Learning Incentive Mechanism Enhanced Gas Usage Estimation ENN Group AAAI 2024 [PUB]
On the Role of Server Momentum in Federated Learning University of Virginia AAAI 2024 [PUB] [PDF]
FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants BUPT AAAI 2024 [PUB] [PAGE] [PDF]
z-SignFedAvg: A Unified Stochastic Sign-Based Compression for Federated Learning CUHK; China Shenzhen Research Institute of Big Data AAAI 2024 [PUB] [PAGE] [PDF]
Data Disparity and Temporal Unavailability Aware Asynchronous Federated Learning for Predictive Maintenance on Transportation Fleets Volkswagen Group AAAI 2024 [PUB] [PAGE]
Federated Graph Learning under Domain Shift with Generalizable Prototypes WHU AAAI 2024 [PUB] [PAGE]
TurboSVM-FL: Boosting Federated Learning through SVM Aggregation for Lazy Clients Technical University of Munich AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Multi-Source Collaborative Gradient Discrepancy Minimization for Federated Domain Generalization TJU AAAI 2024 [PUB] [PDF] [CODE]
Concealing Sensitive Samples against Gradient Leakage in Federated Learning Monash University AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise HUST AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Federated Causality Learning with Explainable Adaptive Optimization SDU AAAI 2024 [PUB] [PAGE] [PDF]
Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users USTC AAAI 2024 [PUB] [PAGE] [PDF]
Exploring One-Shot Semi-supervised Federated Learning with Pre-trained Diffusion Models FDU AAAI 2024 [PUB] [PDF]
Diversity-Authenticity Co-constrained Stylization for Federated Domain Generalization in Person Re-identification XMU; University of Trento AAAI 2024 [PUB] [PAGE]
PerFedRLNAS: One-for-All Personalized Federated Neural Architecture Search U of T AAAI 2024 [PUB] [PAGE]
Efficient Asynchronous Federated Learning with Prospective Momentum Aggregation and Fine-Grained Correction BUPT AAAI 2024 [PUB] [PAGE]
Adversarial Attacks on Federated-Learned Adaptive Bitrate Algorithms HKU AAAI 2024 [PUB]
FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning SJTU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
LR-XFL: Logical Reasoning-Based Explainable Federated Learning NTU AAAI 2024 [PUB] [PDF] [CODE]
A Huber Loss Minimization Approach to Byzantine Robust Federated Learning Zhejiang Lab AAAI 2024 [PUB] [PAGE] [PDF]
Knowledge-Aware Parameter Coaching for Personalized Federated Learning Northeastern University AAAI 2024 [PUB] [PAGE]
Federated Label-Noise Learning with Local Diversity Product Regularization SJTU AAAI 2024 [PUB] [PAGE] [SUPP]
Adapted Weighted Aggregation in Federated Learning (Student Abstract) UBC AAAI 2024 [PUB]
Knowledge Transfer via Compact Model in Federated Learning (Student Abstract) University of Sydney AAAI 2024 [PUB] [PAGE]
PICSR: Prototype-Informed Cross-Silo Router for Federated Learning (Student Abstract) The Ohio State University Auton Lab, CMU AAAI 2024 [PUB] [PAGE]
Privacy-preserving graph convolution network for federated item recommendation SZU AI 2023 [PUB]
Win-Win: A Privacy-Preserving Federated Framework for Dual-Target Cross-Domain Recommendation CAS; UCAS; JD Technology; JD Intelligent Cities Research AAAI 2023 [PUB]
Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense USTC; State Key Laboratory of Cognitive Intelligence AAAI 2023 [PUB] [PDF] [CODE]
Incentive-Boosted Federated Crowdsourcing SDU AAAI 2023 [PUB] [PDF]
Tackling Data Heterogeneity in Federated Learning with Class Prototypes Lehigh University AAAI 2023 [PUB] [PDF] [CODE]
FairFed: Enabling Group Fairness in Federated Learning USC AAAI 2023 [PUB] [PDF] [解读]
Federated Robustness Propagation: Sharing Adversarial Robustness in Heterogeneous Federated Learning MSU AAAI 2023 [PUB]
Complement Sparsification: Low-Overhead Model Pruning for Federated Learning NJIT AAAI 2023 [PUB]
Almost Cost-Free Communication in Federated Best Arm Identification NUS AAAI 2023 [PUB] [PDF]
Layer-Wise Adaptive Model Aggregation for Scalable Federated Learning University of Southern California Inha University AAAI 2023 [PUB] [PDF]
Poisoning with Cerberus: Stealthy and Colluded Backdoor Attack against Federated Learning BJTU AAAI 2023 [PUB]
FedMDFG: Federated Learning with Multi-Gradient Descent and Fair Guidance CUHK; The Shenzhen Institute of Artificial Intelligence and Robotics for Society AAAI 2023 [PUB]
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning USC AAAI 2023 [PUB] [PDF] [VIDEO] [CODE]
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing UTS AAAI 2023 [PUB] [PDF] [CODE]
Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles between Client Data Subspaces UCSD AAAI 2023 [PUB] [PDF] [CODE]
FedABC: Targeting Fair Competition in Personalized Federated Learning WHU; Hubei Luojia Laboratory; JD Explore Academy AAAI 2023 [PUB] [PDF]
Beyond ADMM: A Unified Client-Variance-Reduced Adaptive Federated Learning Framework SUTD AAAI 2023 [PUB] [PDF]
FedGS: Federated Graph-Based Sampling with Arbitrary Client Availability XMU AAAI 2023 [PUB] [PDF] [CODE]
Faster Adaptive Federated Learning University of Pittsburgh AAAI 2023 [PUB] [PDF]
FedNP: Towards Non-IID Federated Learning via Federated Neural Propagation HKUST AAAI 2023 [PUB] [CODE] [VIDEO] [SUPP]
Bayesian Federated Neural Matching That Completes Full Information TJU AAAI 2023 [PUB] [PDF]
CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems ZJU AAAI 2023 [PUB] [PDF] [CODE]
Federated Generative Model on Multi-Source Heterogeneous Data in IoT GSU AAAI 2023 [PUB]
DeFL: Defending against Model Poisoning Attacks in Federated Learning via Critical Learning Periods Awareness SUNY-Binghamton University AAAI 2023 [PUB]
FedALA: Adaptive Local Aggregation for Personalized Federated Learning SJTU AAAI 2023 [PUB] [PDF] [CODE]
Delving into the Adversarial Robustness of Federated Learning ZJU AAAI 2023 [PUB] [PDF]
On the Vulnerability of Backdoor Defenses for Federated Learning TJU AAAI 2023 [PUB] [PDF] [CODE]
Echo of Neighbors: Privacy Amplification for Personalized Private Federated Learning with Shuffle Model RUC; Engineering Research Center of Ministry of Education on Database and BI AAAI 2023 [PUB] [PDF]
DPAUC: Differentially Private AUC Computation in Federated Learning ByteDance Inc. AAAI Special Tracks 2023 [PUB] [PDF] [CODE]
Efficient Training of Large-Scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout NTU AAAI Special Programs 2023 [PUB] [PDF]
Industry-Scale Orchestrated Federated Learning for Drug Discovery KU Leuven AAAI Special Programs 2023 [PUB] [PDF] [VIDEO]
A Federated Learning Monitoring Tool for Self-Driving Car Simulation (Student Abstract) CNU AAAI Special Programs 2023 [PUB]
MGIA: Mutual Gradient Inversion Attack in Multi-Modal Federated Learning (Student Abstract) PolyU AAAI Special Programs 2023 [PUB]
Clustered Federated Learning for Heterogeneous Data (Student Abstract) RUC AAAI Special Programs 2023 [PUB]
FedSampling: A Better Sampling Strategy for Federated Learning THU IJCAI 2023 [PUB] [PDF] [CODE]
HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning ZJU IJCAI 2023 [PUB] [PDF]
FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning NTU IJCAI 2023 [PUB] [PDF] [CODE]
Federated Probabilistic Preference Distribution Modelling with Compactness Co-Clustering for Privacy-Preserving Multi-Domain Recommendation ZJU IJCAI 2023 [PUB]
Federated Graph Semantic and Structural Learning WHU IJCAI 2023 [PUB]
BARA: Efficient Incentive Mechanism with Online Reward Budget Allocation in Cross-Silo Federated Learning SYSU IJCAI 2023 [PUB] [PDF]
FedDWA: Personalized Federated Learning with Dynamic Weight Adjustment SYSU IJCAI 2023 [PUB] [PDF]
FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation Webank IJCAI 2023 [PUB] [PDF]
Globally Consistent Federated Graph Autoencoder for Non-IID Graphs FZU IJCAI 2023 [PUB] [CODE]
Competitive-Cooperative Multi-Agent Reinforcement Learning for Auction-based Federated Learning NTU IJCAI 2023 [PUB]
Dual Personalization on Federated Recommendation JLU; University of Technology Sydney IJCAI 2023 [PUB] [PDF] [CODE]
FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity HUST IJCAI 2023 [PUB] [PDF] [CODE]
Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning Xiangtan University IJCAI 2023 [PUB] [PDF] [CODE]
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks CUHK IJCAI 2023 [PUB] [PDF] [CODE]
FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer Ping An Technology; THU IJCAI 2023 [PUB] [PDF]
Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data UTS IJCAI 2023 [PUB] [PDF] [CODE]
FedBFPT: An Efficient Federated Learning Framework for Bert Further Pre-training ZJU IJCAI 2023 [PUB] [CODE]
Bayesian Federated Learning: A Survey IJCAI Survey Track 2023 [PDF]
A Survey of Federated Evaluation in Federated Learning Macquarie University IJCAI Survey Track 2023 [PUB] [PDF]
SAMBA: A Generic Framework for Secure Federated Multi-Armed Bandits (Extended Abstract) INSA Centre Val de Loire IJCAI Journal Track 2023 [PUB]
The communication cost of security and privacy in federated frequency estimation Stanford AISTATS 2023 [PUB] [CODE]
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout Rice University AISTATS 2023 [PUB] [CODE]
Federated Learning under Distributed Concept Drift CMU AISTATS 2023 [PUB] [CODE]
Characterizing Internal Evasion Attacks in Federated Learning CMU AISTATS 2023 [PUB] [CODE]
Federated Asymptotics: a model to compare federated learning algorithms Stanford AISTATS 2023 [PUB] [CODE]
Private Non-Convex Federated Learning Without a Trusted Server USC AISTATS 2023 [PUB] [CODE]
Federated Learning for Data Streams Universit ́ e Cˆ ote d’Azur AISTATS 2023 [PUB] [CODE]
Nothing but Regrets — Privacy-Preserving Federated Causal Discovery Helmholtz Centre for Information Security AISTATS 2023 [PUB] [CODE]
Active Membership Inference Attack under Local Differential Privacy in Federated Learning UFL AISTATS 2023 [PUB] [CODE]
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms CMAP AISTATS 2023 [PUB]
Byzantine-Robust Federated Learning with Optimal Statistical Rates UC Berkeley AISTATS 2023 [PUB] [CODE]
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing UTS AAAI 2023 [PDF] [CODE]
FedGS: Federated Graph-based Sampling with Arbitrary Client Availability XMU AAAI 2023 [PDF] [CODE]
Incentive-boosted Federated Crowdsourcing SDU AAAI 2023 [PDF]
Towards Understanding Biased Client Selection in Federated Learning. CMU AISTATS 2022 [PUB] [CODE]
FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning KAUST AISTATS 2022 [PUB] [PDF] [CODE]
Sharp Bounds for Federated Averaging (Local SGD) and Continuous Perspective. Stanford AISTATS 2022 [PUB] [PDF] [CODE]
Federated Reinforcement Learning with Environment Heterogeneity. PKU AISTATS 2022 [PUB] [PDF] [CODE]
Federated Myopic Community Detection with One-shot Communication Purdue AISTATS 2022 [PUB] [PDF]
Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits. University of Virginia AISTATS 2022 [PUB] [PDF] [CODE]
Towards Federated Bayesian Network Structure Learning with Continuous Optimization. CMU AISTATS 2022 [PUB] [PDF] [CODE]
Federated Learning with Buffered Asynchronous Aggregation Meta AI AISTATS 2022 [PUB] [PDF] [VIDEO]
Differentially Private Federated Learning on Heterogeneous Data. Stanford AISTATS 2022 [PUB] [PDF] [CODE]
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification Princeton AISTATS 2022 [PUB] [PDF] [CODE] [VIDEO]
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning KAUST AISTATS 2022 [PUB] [PDF]
Federated Functional Gradient Boosting. University of Pennsylvania AISTATS 2022 [PUB] [PDF] [CODE]
QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning. Criteo AI Lab AISTATS 2022 [PUB] [PDF] [CODE] [VIDEO]
Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting kg. ZJU IJCAI 2022 [PUB] [PDF] [CODE]
Personalized Federated Learning With a Graph UTS IJCAI 2022 [PUB] [PDF] [CODE]
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification ZJU IJCAI 2022 [PUB] [PDF]
Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learning IJCAI 2022 [PUB] [PDF] [CODE]
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning IJCAI 2022 [PUB] [PDF]
Private Semi-Supervised Federated Learning. IJCAI 2022 [PUB]
Continual Federated Learning Based on Knowledge Distillation. IJCAI 2022 [PUB]
Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features IJCAI 2022 [PUB] [PDF] [CODE]
Federated Multi-Task Attention for Cross-Individual Human Activity Recognition IJCAI 2022 [PUB]
Personalized Federated Learning with Contextualized Generalization. IJCAI 2022 [PUB] [PDF]
Shielding Federated Learning: Robust Aggregation with Adaptive Client Selection. IJCAI 2022 [PUB] [PDF]
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning IJCAI 2022 [PUB] [PDF] [CODE]
FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server. IJCAI 2022 [PUB] [PDF]
Towards Verifiable Federated Learning surv. IJCAI 2022 [PUB] [PDF]
HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images CUHK; BUAA AAAI 2022 [PUB] [PDF] [CODE] [解读]
Federated Learning for Face Recognition with Gradient Correction BUPT AAAI 2022 [PUB] [PDF]
SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data USC AAAI 2022 [PUB] [PDF] [CODE] [解读]
SmartIdx: Reducing Communication Cost in Federated Learning by Exploiting the CNNs Structures HIT; PCL AAAI 2022 [PUB] [CODE]
Bridging between Cognitive Processing Signals and Linguistic Features via a Unified Attentional Network TJU AAAI 2022 [PUB] [PDF]
Seizing Critical Learning Periods in Federated Learning SUNY-Binghamton University AAAI 2022 [PUB] [PDF]
Coordinating Momenta for Cross-silo Federated Learning University of Pittsburgh AAAI 2022 [PUB] [PDF]
FedProto: Federated Prototype Learning over Heterogeneous Devices UTS AAAI 2022 [PUB] [PDF] [CODE]
FedSoft: Soft Clustered Federated Learning with Proximal Local Updating CMU AAAI 2022 [PUB] [PDF] [CODE]
Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better The University of Texas at Austin AAAI 2022 [PUB] [PDF] [CODE]
FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition National Taiwan University AAAI 2022 [PUB] [PDF] [CODE]
SplitFed: When Federated Learning Meets Split Learning CSIRO AAAI 2022 [PUB] [PDF] [CODE]
Efficient Device Scheduling with Multi-Job Federated Learning Soochow University AAAI 2022 [PUB] [PDF]
Implicit Gradient Alignment in Distributed and Federated Learning IIT Kanpur AAAI 2022 [PUB] [PDF]
Federated Nearest Neighbor Classification with a Colony of Fruit-Flies IBM Research AAAI 2022 [PUB] [PDF] [CODE]
Iterated Vector Fields and Conservatism, with Applications to Federated Learning. Google ALT 2022 [PUB] [PDF]
Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization IJCAI 2021 [PUB] [PDF] [VIDEO]
Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning IJCAI 2021 [PUB] [PDF]
FedSpeech: Federated Text-to-Speech with Continual Learning IJCAI 2021 [PUB] [PDF]
Practical One-Shot Federated Learning for Cross-Silo Setting IJCAI 2021 [PUB] [PDF] [CODE]
Federated Model Distillation with Noise-Free Differential Privacy IJCAI 2021 [PUB] [PDF] [VIDEO]
LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy IJCAI 2021 [PUB] [PDF]
Federated Learning with Fair Averaging. 🔥 IJCAI 2021 [PUB] [PDF] [CODE]
H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning. IJCAI 2021 [PUB] [PDF]
Communication-efficient and Scalable Decentralized Federated Edge Learning. IJCAI 2021 [PUB]
Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating Xidian University; JD Tech AAAI 2021 [PUB] [PDF] [VIDEO]
FedRec++: Lossless Federated Recommendation with Explicit Feedback SZU AAAI 2021 [PUB] [VIDEO]
Federated Multi-Armed Bandits University of Virginia AAAI 2021 [PUB] [PDF] [CODE] [VIDEO]
On the Convergence of Communication-Efficient Local SGD for Federated Learning Temple University; University of Pittsburgh AAAI 2021 [PUB] [VIDEO]
FLAME: Differentially Private Federated Learning in the Shuffle Model Renmin University of China; Kyoto University AAAI 2021 [PUB] [PDF] [VIDEO] [CODE]
Toward Understanding the Influence of Individual Clients in Federated Learning SJTU; The University of Texas at Dallas AAAI 2021 [PUB] [PDF] [VIDEO]
Provably Secure Federated Learning against Malicious Clients Duke University AAAI 2021 [PUB] [PDF] [VIDEO] [SLIDE]
Personalized Cross-Silo Federated Learning on Non-IID Data Simon Fraser University; McMaster University AAAI 2021 [PUB] [PDF] [VIDEO] [UC.]
Model-Sharing Games: Analyzing Federated Learning under Voluntary Participation Cornell University AAAI 2021 [PUB] [PDF] [CODE] [VIDEO]
Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning University of Nevada; IBM Research AAAI 2021 [PUB] [PDF] [VIDEO]
Game of Gradients: Mitigating Irrelevant Clients in Federated Learning IIT Bombay; IBM Research AAAI 2021 [PUB] [PDF] [CODE] [VIDEO] [SUPP]
Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models CUHK; Arizona State University AAAI 2021 [PUB] [PDF] [VIDEO] [CODE]
Addressing Class Imbalance in Federated Learning Northwestern University AAAI 2021 [PUB] [PDF] [VIDEO] [CODE] [解读]
Defending against Backdoors in Federated Learning with Robust Learning Rate The University of Texas at Dallas AAAI 2021 [PUB] [PDF] [VIDEO] [CODE]
Free-rider Attacks on Model Aggregation in Federated Learning Accenture Labs AISTATS 2021 [PUB] [PDF] [CODE] [VIDEO] [SUPP]
Federated f-differential privacy University of Pennsylvania AISTATS 2021 [PUB] [CODE] [VIDEO] [SUPP]
Federated learning with compression: Unified analysis and sharp guarantees 🔥 The Pennsylvania State University; The University of Texas at Austin AISTATS 2021 [PUB] [PDF] [CODE] [VIDEO] [SUPP]
Shuffled Model of Differential Privacy in Federated Learning UCLA; Google AISTATS 2021 [PUB] [VIDEO] [SUPP]
Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning Google AISTATS 2021 [PUB] [PDF] [VIDEO] [SUPP]
Federated Multi-armed Bandits with Personalization University of Virginia; The Pennsylvania State University AISTATS 2021 [PUB] [PDF] [CODE] [VIDEO] [SUPP]
Towards Flexible Device Participation in Federated Learning CMU; SYSU AISTATS 2021 [PUB] [PDF] [VIDEO] [SUPP]
Federated Meta-Learning for Fraudulent Credit Card Detection IJCAI 2020 [PUB] [VIDEO]
A Multi-player Game for Studying Federated Learning Incentive Schemes IJCAI 2020 [PUB] [CODE] [解读]
Practical Federated Gradient Boosting Decision Trees NUS; UWA AAAI 2020 [PUB] [PDF] [CODE]
Federated Learning for Vision-and-Language Grounding Problems PKU; Tencent AAAI 2020 [PUB]
Federated Latent Dirichlet Allocation: A Local Differential Privacy Based Framework BUAA AAAI 2020 [PUB]
Federated Patient Hashing Cornell University AAAI 2020 [PUB]
Robust Federated Learning via Collaborative Machine Teaching Symantec Research Labs; KAUST AAAI 2020 [PUB] [PDF]
FedVision: An Online Visual Object Detection Platform Powered by Federated Learning WeBank AAAI 2020 [PUB] [PDF] [CODE]
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization UC Santa Barbara; UT Austin AISTATS 2020 [PUB] [PDF] [VIDEO] [SUPP]
How To Backdoor Federated Learning 🔥 Cornell Tech AISTATS 2020 [PUB] [PDF] [VIDEO] [CODE] [SUPP]
Federated Heavy Hitters Discovery with Differential Privacy RPI; Google AISTATS 2020 [PUB] [PDF] [VIDEO] [SUPP]
Multi-Agent Visualization for Explaining Federated Learning WeBank IJCAI 2019 [PUB] [VIDEO]

fl in top ml conference and journal

Federated Learning papers accepted by top ML(machine learning) conference and journal, Including NeurIPS(Annual Conference on Neural Information Processing Systems), ICML(International Conference on Machine Learning), ICLR(International Conference on Learning Representations), COLT(Annual Conference Computational Learning Theory) , UAI(Conference on Uncertainty in Artificial Intelligence),Machine Learning, JMLR(Journal of Machine Learning Research), TPAMI(IEEE Transactions on Pattern Analysis and Machine Intelligence).

fl in top ml conference and journal
Title Affiliation Venue Year Materials
One-shot Federated Learning via Synthetic Distiller-Distillate Communication NeurIPS 2024 [PUB]
Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data NeurIPS 2024 [PUB]
FedGMKD: An Efficient Prototype Federated Learning Framework through Knowledge Distillation and Discrepancy-Aware Aggregation NeurIPS 2024 [PUB]
Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach NeurIPS 2024 [PUB]
Federated Model Heterogeneous Matryoshka Representation Learning NeurIPS 2024 [PUB]
Federated Graph Learning for Cross-Domain Recommendation NeurIPS 2024 [PUB]
FedGMark: Certifiably Robust Watermarking for Federated Graph Learning NeurIPS 2024 [PUB]
Dual-Personalizing Adapter for Federated Foundation Models NeurIPS 2024 [PUB]
Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning NeurIPS 2024 [PUB]
Taming the Long Tail in Human Mobility Prediction NeurIPS 2024 [PUB]
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning NeurIPS 2024 [PUB]
Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution NeurIPS 2024 [PUB]
DoFIT: Domain-aware Federated Instruction Tuning with Alleviated Catastrophic Forgetting NeurIPS 2024 [PUB]
Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability NeurIPS 2024 [PUB]
Federated Transformer: Multi-Party Vertical Federated Learning on Practical Fuzzily Linked Data NeurIPS 2024 [PUB]
FIARSE: Model-Heterogeneous Federated Learning via Importance-Aware Submodel Extraction NeurIPS 2024 [PUB]
Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data NeurIPS 2024 [PUB]
FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations NeurIPS 2024 [PUB]
Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains NeurIPS 2024 [PUB]
pFedClub: Controllable Heterogeneous Model Aggregation for Personalized Federated Learning NeurIPS 2024 [PUB]
Why Go Full? Elevating Federated Learning Through Partial Network Updates NeurIPS 2024 [PUB]
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion NeurIPS 2024 [PUB]
FedSSP: Federated Graph Learning with Spectral Knowledge and Personalized Preference NeurIPS 2024 [PUB]
Handling Learnwares from Heterogeneous Feature Spaces with Explicit Label Exploitation NeurIPS 2024 [PUB]
A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs NeurIPS 2024 [PUB]
Private and Personalized Frequency Estimation in a Federated Setting NeurIPS 2024 [PUB]
The Sample-Communication Complexity Trade-off in Federated Q-Learning NeurIPS 2024 [PUB]
Federated Ensemble-Directed Offline Reinforcement Learning NeurIPS 2024 [PUB]
Federated Black-Box Adaptation for Semantic Segmentation NeurIPS 2024 [PUB]
Thinking Forward: Memory-Efficient Federated Finetuning of Language Models NeurIPS 2024 [PUB]
Federated Learning from Vision-Language Foundation Models: Theoretical Analysis and Method NeurIPS 2024 [PUB]
Optimal Design for Human Preference Elicitation NeurIPS 2024 [PUB]
Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration NeurIPS 2024 [PUB]
Personalized Federated Learning via Feature Distribution Adaptation NeurIPS 2024 [PUB]
SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning NeurIPS 2024 [PUB]
A Bayesian Approach for Personalized Federated Learning in Heterogeneous Settings NeurIPS 2024 [PUB]
RFLPA: A Robust Federated Learning Framework against Poisoning Attacks with Secure Aggregation NeurIPS 2024 [PUB]
FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning NeurIPS 2024 [PUB]
End-to-end Learnable Clustering for Intent Learning in Recommendation NeurIPS 2024 [PUB]
FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation NeurIPS 2024 [PUB]
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting NeurIPS 2024 [PUB]
FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection NeurIPS 2024 [PUB]
A Swiss Army Knife for Heterogeneous Federated Learning: Flexible Coupling via Trace Norm NeurIPS 2024 [PUB]
FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reduction NeurIPS 2024 [PUB]
Low Precision Local Training is Enough for Federated Learning NeurIPS 2024 [PUB]
Resource-Aware Federated Self-Supervised Learning with Global Class Representations NeurIPS 2024 [PUB]
On the Necessity of Collaboration for Online Model Selection with Decentralized Data NeurIPS 2024 [PUB]
The Power of Extrapolation in Federated Learning NeurIPS 2024 [PUB]
(FL)$^2$: Overcoming Few Labels in Federated Semi-Supervised Learning NeurIPS 2024 [PUB]
On Sampling Strategies for Spectral Model Sharding NeurIPS 2024 [PUB]
Customizing Language Models with Instance-wise LoRA for Sequential Recommendation NeurIPS 2024 [PUB]
SpaFL: Communication-Efficient Federated Learning With Sparse Models And Low Computational Overhead NeurIPS 2024 [PUB]
HYDRA-FL: Hybrid Knowledge Distillation for Robust and Accurate Federated Learning NeurIPS 2024 [PUB]
Stabilized Proximal-Point Methods for Federated Optimization NeurIPS 2024 [PUB]
DapperFL: Domain Adaptive Federated Learning with Model Fusion Pruning for Edge Devices NeurIPS 2024 [PUB]
Parameter Disparities Dissection for Backdoor Defense in Heterogeneous Federated Learning NeurIPS 2024 [PUB]
Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD NeurIPS 2024 [PUB]
FedAvP: Augment Local Data via Shared Policy in Federated Learning NeurIPS 2024 [PUB]
CoBo: Collaborative Learning via Bilevel Optimization NeurIPS 2024 [PUB]
Convergence Analysis of Split Federated Learning on Heterogeneous Data NeurIPS 2024 [PUB]
Communication-Efficient Federated Group Distributionally Robust Optimization NeurIPS 2024 [PUB]
Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity NeurIPS 2024 [PUB]
Federated Learning over Connected Modes NeurIPS 2024 [PUB]
Personalized Federated Learning with Mixture of Models for Adaptive Prediction and Model Fine-Tuning NeurIPS 2024 [PUB]
Does Egalitarian Fairness Lead to Instability? The Fairness Bounds in Stable Federated Learning Under Altruistic Behaviors NeurIPS 2024 [PUB]
Federated Online Prediction from Experts with Differential Privacy: Separations and Regret Speed-ups NeurIPS 2024 [PUB]
DataStealing: Steal Data from Diffusion Models in Federated Learning with Multiple Trojans NeurIPS 2024 [PUB]
Federated Behavioural Planes: Explaining the Evolution of Client Behaviour in Federated Learning NeurIPS 2024 [PUB]
Hierarchical Federated Learning with Multi-Timescale Gradient Correction NeurIPS 2024 [PUB]
HyperPrism: An Adaptive Non-linear Aggregation Framework for Distributed Machine Learning over Non-IID Data and Time-varying Communication Links NeurIPS 2024 [PUB]
SPEAR: Exact Gradient Inversion of Batches in Federated Learning NeurIPS 2024 [PUB]
Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis NeurIPS 2024 [PUB]
Bridging Gaps: Federated Multi-View Clustering in Heterogeneous Hybrid Views NeurIPS 2024 [PUB]
Confusion-Resistant Federated Learning via Diffusion-Based Data Harmonization on Non-IID Data NeurIPS 2024 [PUB]
Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning NeurIPS 2024 [PUB]
Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning NeurIPS 2024 [PUB]
Classifier Clustering and Feature Alignment for Federated Learning under Distributed Concept Drift NeurIPS 2024 [PUB]
Heterogeneity-Guided Client Sampling: Towards Fast and Efficient Non-IID Federated Learning NeurIPS 2024 [PUB]
FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding? NeurIPS 2024 [PUB]
Active preference learning for ordering items in- and out-of-sample NeurIPS 2024 [PUB]
Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources NeurIPS 2024 [PUB]
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients NeurIPS 2024 [PUB]
Revisiting Ensembling in One-Shot Federated Learning NeurIPS 2024 [PUB]
FedLLM-Bench: Realistic Benchmarks for Federated Learning of Large Language Models NeurIPS 2024 [PUB]
$ exttt{pfl-research}$: simulation framework for accelerating research in Private Federated Learning NeurIPS 2024 [PUB]
FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection NeurIPS 2024 [PUB]
Momentum Approximation in Asynchronous Private Federated Learning NeurIPS workshop 2024 [PUB]
Cohort Squeeze: Beyond a Single Communication Round per Cohort in Cross-Device Federated Learning NeurIPS workshop 2024 [PUB]
Federated Learning with Generative Content NeurIPS workshop 2024 [PUB]
Leveraging Unstructured Text Data for Federated Instruction Tuning of Large Language Models NeurIPS workshop 2024 [PUB]
Emerging Safety Attack and Defense in Federated Instruction Tuning of Large Language Models NeurIPS workshop 2024 [PUB]
Defection-Free Collaboration between Competitors in a Learning System NeurIPS workshop 2024 [PUB]
On the Convergence Rates of Federated Q-Learning across Heterogeneous Environments NeurIPS workshop 2024 [PUB]
EncCluster: Bringing Functional Encryption in Federated Foundational Models NeurIPS workshop 2024 [PUB]
Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models NeurIPS workshop 2024 [PUB]
Hot Pluggable Federated Learning NeurIPS workshop 2024 [PUB]
Federated Dynamical Low-Rank Training with Global Loss Convergence Guarantees NeurIPS workshop 2024 [PUB]
The Future of Large Language Model Pre-training is Federated NeurIPS workshop 2024 [PUB]
Collaborative Learning with Shared Linear Representations: Statistical Rates and Optimal Algorithms NeurIPS workshop 2024 [PUB]
The SynapticCity Phenomenon: When All Foundation Models Marry Federated Learning and Blockchain NeurIPS workshop 2024 [PUB]
ZOOPFL: Exploring Black-box Foundation Models for Personalized Federated Learning NeurIPS workshop 2024 [PUB]
DeComFL: Federated Learning with Dimension-Free Communication NeurIPS workshop 2024 [PUB]
Improving Group Connectivity for Generalization of Federated Deep Learning NeurIPS workshop 2024 [PUB]
MAP: Model Merging with Amortized Pareto Front Using Limited Computation NeurIPS workshop 2024 [PUB]
OPA: One-shot Private Aggregation with Single Client Interaction and its Applications to Federated Learning NeurIPS workshop 2024 [PUB]
Adaptive Hybrid Model Pruning in Federated Learning through Loss Exploration NeurIPS workshop 2024 [PUB]
Worldwide Federated Training of Language Models NeurIPS workshop 2024 [PUB]
FedStein: Enhancing Multi-Domain Federated Learning Through James-Stein Estimator NeurIPS workshop 2024 [PUB]
Enhancing Causal Discovery in Federated Settings with Limited Local Samples NeurIPS workshop 2024 [PUB]
$ exttt{pfl-research}$: simulation framework for accelerating research in Private Federated Learning NeurIPS workshop 2024 [PUB]
DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning using Packed Secret Sharing NeurIPS workshop 2024 [PUB]
FedCBO: Reaching Group Consensus in Clustered Federated Learning through Consensus-based Optimization JMLR 2024 [PUB]
Effective Federated Graph Matching ICML 2024 [PUB]
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation ICML 2024 [PUB]
Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients ICML 2024 [PUB]
FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models ICML 2024 [PUB]
Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning ICML 2024 [PUB]
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization ICML 2024 [PUB]
Enhancing Storage and Computational Efficiency in Federated Multimodal Learning for Large-Scale Models ICML 2024 []
Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments ICML 2024 [PUB]
Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates ICML 2024 [PUB]
Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective ICML 2024 [PUB]
Accelerating Federated Learning with Quick Distributed Mean Estimation ICML 2024 [PUB]
Fair Federated Learning via the Proportional Veto Core ICML 2024 [PUB]
AegisFL: Efficient and Flexible Privacy-Preserving Byzantine-Robust Cross-silo Federated Learning ICML 2024 [PUB]
Recovering Labels from Local Updates in Federated Learning ICML 2024 [PUB]
FedMBridge: Bridgeable Multimodal Federated Learning ICML 2024 [PUB]
Harmonizing Generalization and Personalization in Federated Prompt Learning ICML 2024 [PUB]
Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization ICML 2024 [PUB]
Accelerating Heterogeneous Federated Learning with Closed-form Classifiers ICML 2024 [PUB]
Federated Combinatorial Multi-Agent Multi-Armed Bandits ICML 2024 [PUB]
A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization ICML 2024 [PUB]
Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses ICML 2024 [PUB]
FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering ICML 2024 [PUB]
Pursuing Overall Welfare in Federated Learning through Sequential Decision Making ICML 2024 [PUB]
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs ICML 2024 [PUB]
Self-Driven Entropy Aggregation for Byzantine-Robust Heterogeneous Federated Learning ICML 2024 [PUB]
Overcoming Data and Model heterogeneities in Decentralized Federated Learning via Synthetic Anchors ICML 2024 [PUB]
Federated Optimization with Doubly Regularized Drift Correction ICML 2024 [PUB]
FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data ICML 2024 [PUB]
Certifiably Byzantine-Robust Federated Conformal Prediction ICML 2024 [PUB]
Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning ICML 2024 [PUB]
Clustered Federated Learning via Gradient-based Partitioning ICML 2024 [PUB]
Recurrent Early Exits for Federated Learning with Heterogeneous Clients ICML 2024 [PUB]
Rethinking the Flat Minima Searching in Federated Learning ICML 2024 [PUB]
FedBAT: Communication-Efficient Federated Learning via Learnable Binarization ICML 2024 [PUB]
Federated Representation Learning in the Under-Parameterized Regime ICML 2024 [PUB]
FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees ICML 2024 [PUB]
Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning ICML 2024 [PUB]
SILVER: Single-loop variance reduction and application to federated learning ICML 2024 [PUB]
SignSGD with Federated Defense: Harnessing Adversarial Attacks through Gradient Sign Decoding ICML 2024 [PUB]
FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler ICML 2024 [PUB]
Federated Continual Learning via Prompt-based Dual Knowledge Transfer ICML 2024 [PUB]
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes ICML 2024 [PUB]
Decomposable Submodular Maximization in Federated Setting ICML 2024 [PUB]
Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems ICML 2024 [PUB]
Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials ICML 2024 [PUB]
Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often! ICML 2024 [PUB]
Byzantine Resilient and Fast Federated Few-Shot Learning ICML 2024 [PUB]
Causally Motivated Personalized Federated Invariant Learning with Shortcut-Averse Information-Theoretic Regularization ICML 2024 [PUB]
Ranking-based Client Imitation Selection for Efficient Federated Learning ICML 2024 [PUB]
Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms ICML 2024 [PUB]
FADAS: Towards Federated Adaptive Asynchronous Optimization ICML 2024 [PUB]
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices ICML 2024 [PUB]
FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error ICML 2024 [PUB]
MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis ICML 2024 [PUB]
Federated Neuro-Symbolic Learning ICML 2024 [PUB]
Adaptive Group Personalization for Federated Mutual Transfer Learning ICML 2024 [PUB]
Balancing Similarity and Complementarity for Federated Learning ICML 2024 [PUB]
Federated Self-Explaining GNNs with Anti-shortcut Augmentations ICML 2024 [PUB]
A Federated Stochastic Multi-level Compositional Minimax Algorithm for Deep AUC Maximization ICML 2024 [PUB]
COALA: A Practical and Vision-Centric Federated Learning Platform ICML 2024 [PUB]
Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization Mach Learn 2024 [PUB]
Communication-efficient clustered federated learning via model distance USTC; State Key Laboratory of Cognitive Intelligence Mach Learn 2024 [PUB]
Federated learning with superquantile aggregation for heterogeneous data. Google Research Mach Learn 2024 [PUB] [PDF] [CODE]
Aligning model outputs for class imbalanced non-IID federated learning NJU Mach Learn 2024 [PUB]
Federated Learning of Generalized Linear Causal Networks TPAMI 2024 [PUB]
Cross-Modal Federated Human Activity Recognition TPAMI 2024 [PUB]
Federated Gaussian Process: Convergence, Automatic Personalization and Multi-Fidelity Modeling Northeastern University; UoM TPAMI 2024 [PUB] [PDF] [CODE]
The Impact of Adversarial Attacks on Federated Learning: A Survey IIT TPAMI 2024 [PUB]
Understanding and Mitigating Dimensional Collapse in Federated Learning NUS TPAMI 2024 [PUB] [PDF] [CODE]
No One Left Behind: Real-World Federated Class-Incremental Learning CAS; UCAS TPAMI 2024 [PUB] [PDF] [CODE]
Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity Learning WHU TPAMI 2024 [PUB] [PDF] [CODE]
Multi-Stage Asynchronous Federated Learning With Adaptive Differential Privacy HPU; XJTU TPAMI 2024 [PUB] [PDF] [CODE]
A Bayesian Federated Learning Framework With Online Laplace Approximation SUSTech TPAMI 2024 [PUB] [PDF] [CODE]
Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting USTC; HKBU ICLR 2024 [PUB]
One-shot Empirical Privacy Estimation for Federated Learning Google ICLR 2024 [PUB] [PDF]
Stochastic Controlled Averaging for Federated Learning with Communication Compression LinkedIn; UPenn ICLR 2024 [PUB] [PDF]
A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging IBM ICLR 2024 [PUB] [PDF] [CODE]
A Mutual Information Perspective on Federated Contrastive Learning QualComm ICLR 2024 [PUB]
Benchmarking Algorithms for Federated Domain Generalization Purdue University ICLR 2024 [PUB] [PDF] [CODE]
Effective and Efficient Federated Tree Learning on Hybrid Data UC Berkeley ICLR 2024 [PUB] [PDF]
Federated Recommendation with Additive Personalization UTS ICLR 2024 [PUB] [PDF] [CODE]
Tackling the Data Heterogeneity in Asynchronous Federated Learning with Cached Update Calibration PSU ICLR 2024 [PUB] [SUPP]
Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning USC ICLR 2024 [PUB] [SUPP] [PDF]
Accurate Forgetting for Heterogeneous Federated Continual Learning THU ICLR 2024 [PUB] [CODE]
Federated Causal Discovery from Heterogeneous Data MBZUAI ICLR 2024 [PUB] [PDF] [CODE]
On Differentially Private Federated Linear Contextual Bandits Wayne State University ICLR 2024 [PUB] [SUPP] [PDF]
Incentivized Truthful Communication for Federated Bandits University of Virginia ICLR 2024 [PUB] [PDF]
Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting UIUC ICLR 2024 [PUB]
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity KAUST ICLR 2024 [PUB]
Text-driven Prompt Generation for Vision-Language Models in Federated Learning Robert Bosch LLC ICLR 2024 [PUB] [PDF]
Improving LoRA in Privacy-preserving Federated Learning Northeastern University ICLR 2024 [PUB]
FedWon: Triumphing Multi-domain Federated Learning Without Normalization Sony AI ICLR 2024 [PUB] [PDF]
FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning TU Delft ICLR 2024 [PUB]
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler ANL; UIUC; NCSA ICLR 2024 [PUB] [PDF] [CODE] [PAGE]
Bayesian Coreset Optimization for Personalized Federated Learning IIT Bombay ICLR 2024 [PUB]
Layer-wise linear mode connectivity Ruhr-Universtät Bochum ICLR 2024 [PUB] [PDF] [SUPP]
Fake It Till Make It: Federated Learning with Consensus-Oriented Generation SJTU ICLR 2024 [PUB] [PDF]
Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning INSAIT ICLR 2024 [PUB] [SUPP] [PDF]
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning Columbia University ICLR 2024 [PUB] [PDF]
Adaptive Federated Learning with Auto-Tuned Clients Rice University ICLR 2024 [PUB] [SUPP] [PDF]
Backdoor Federated Learning by Poisoning Backdoor-Critical Layers ND ICLR 2024 [PUB] [SUPP] [PDF]
Federated Q-Learning: Linear Regret Speedup with Low Communication Cost PSU ICLR 2024 [PUB] [SUPP] [PDF]
FedImpro: Measuring and Improving Client Update in Federated Learning HKBU ICLR 2024 [PUB] [PDF]
Federated Wasserstein Distance MIT ICLR 2024 [PUB] [SUPP] [PDF]
An improved analysis of per-sample and per-update clipping in federated learning DTU ICLR 2024 [PUB]
FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation NTU ICLR 2024 [PUB] [SUPP]
Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning HKU ICLR 2024 [PUB] [PDF]
Momentum Benefits Non-iid Federated Learning Simply and Provably PKU; UPenn ICLR 2024 [PUB] [PDF]
Communication-Efficient Federated Non-Linear Bandit Optimization Yale University ICLR 2024 [PUB] [PDF]
Fair and Efficient Contribution Valuation for Vertical Federated Learning Huawei ICLR 2024 [PUB] [SUPP] [PDF] [CODE]
Demystifying Local & Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition UMCP ICLR 2024 [PUB] [PDF]
Learning Personalized Causally Invariant Representations for Heterogeneous Federated Clients PolyU ICLR 2024 [PUB]
PeFLL: Personalized Federated Learning by Learning to Learn IST ICLR 2024 [PUB] [SUPP] [PDF]
Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates JHU ICLR 2024 [PUB] [SUPP] [PDF]
FedInverse: Evaluating Privacy Leakage in Federated Learning USQ ICLR 2024 [PUB] [SUPP]
FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization UMCP ICLR 2024 [PUB] [SUPP] [PDF]
Robust Training of Federated Models with Extremely Label Deficiency HKBU ICLR 2024 [PUB] [PDF] [CODE]
Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory RIKEN AIP ICLR 2024 [PUB]
Teach LLMs to Phish: Stealing Private Information from Language Models Princeton University ICLR 2024 [PUB]
Like Oil and Water: Group Robustness Methods and Poisoning Defenses Don't Mix UMCP ICLR 2024 [PUB]
Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise HKUST ICLR 2024 [PUB] [PDF]
Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks CAS ICLR 2024 [PUB] [SUPP] [PDF] [CODE]
Local Composite Saddle Point Optimization Purdue University ICLR 2024 [PUB] [PDF]
Enhancing Neural Training via a Correlated Dynamics Model TIIT ICLR 2024 [PUB] [PDF]
EControl: Fast Distributed Optimization with Compression and Error Control Saarland University ICLR 2024 [PUB] [SUPP] [PDF]
Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit HKUST ICLR 2024 [PUB]
FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent UMCP ICLR 2024 [PUB] [SUPP] [PDF] [CODE]
Heterogeneous Personalized Federated Learning by Local-Global Updates Mixing via Convergence Rate CUHK ICLR 2024 [PUB]
Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages University of Cambridge ICLR 2024 [PUB]
Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity NTT DATA Mathematical Systems Inc. ICLR 2024 [PUB]
VFLAIR: A Research Library and Benchmark for Vertical Federated Learning THU ICLR 2024 [PUB] [PDF] [CODE]
Incentive-Aware Federated Learning with Training-Time Model Rewards NUS ICLR 2024 [PUB] [SUPP]
VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning Benchmarks NUS ICLR 2024 [PUB] [PDF] [CODE]
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data ZJU ICLR 2024 [PUB] [SUPP] [PDF]
SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning University at Buffalo NeurIPS 2023 [PUB] [PDF] [SUPP]
Mechanism Design for Collaborative Normal Mean Estimation UW-Madison NeurIPS 2023 [PUB] [PDF]
Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity EPFL NeurIPS 2023 [PUB] [PDF] [CODE]
Incentives in Federated Learning: Equilibria, Dynamics, and Mechanisms for Welfare Maximization UIUC NeurIPS 2023 [PUB] [SUPP]
Convergence Analysis of Sequential Federated Learning on Heterogeneous Data BUPT NeurIPS 2023 [PUB] [PDF] [CODE]
Handling Data Heterogeneity via Architectural Design for Federated Visual Recognition MBZUAI NeurIPS 2023 [PUB] [PDF] [CODE]
Private Federated Frequency Estimation: Adapting to the Hardness of the Instance JHU NeurIPS 2023 [PUB] [SUPP] [PDF]
Zeroth-Order Methods for Nondifferentiable, Nonconvex, and Hierarchical Federated Optimization Rutgers University NeurIPS 2023 [PUB] [SUPP] [PDF]
Incentivized Communication for Federated Bandits University of Virginia NeurIPS 2023 [PUB] [PDF]
Multiply Robust Federated Estimation of Targeted Average Treatment Effects Northeastern University NeurIPS 2023 [PUB] [PDF]
IBA: Towards Irreversible Backdoor Attacks in Federated Learning Vanderbilt University; VinUniversity NeurIPS 2023 [PUB] [SUPP] [CODE]
EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning KAIST NeurIPS 2023 [PUB] [SUPP] [PDF]
Federated Linear Bandits with Finite Adversarial Actions University of Virginia NeurIPS 2023 [PUB] [SUPP] [PDF]
FedNAR: Federated Optimization with Normalized Annealing Regularization MBZUAI NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Guiding The Last Layer in Federated Learning with Pre-Trained Models Concordia University NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization HZAU NeurIPS 2023 [PUB] [SUPP]
Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Approach for Object Detection KAIST NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks USC NeurIPS 2023 [PUB] [PDF] [CODE]
Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning UTS NeurIPS 2023 [PUB] [SUPP]
One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning Rice University NeurIPS 2023 [PUB] [SUPP] [CODE]
Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training Gatech NeurIPS 2023 [PUB] [SUPP] [CODE]
FedGame: A Game-Theoretic Defense against Backdoor Attacks in Federated Learning PSU; UIUC NeurIPS 2023 [PUB] [SUPP] [CODE]
Towards Personalized Federated Learning via Heterogeneous Model Reassembly PSU NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction GWU NeurIPS 2023 [PUB] [SUPP] [PDF]
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning ECNU NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning Western University NeurIPS 2023 [PUB] [SUPP] [CODE]
RECESS Vaccine for Federated Learning: Proactive Defense Against Model Poisoning Attacks Xidian University; University of Guelph; Zhejiang Key Laboratory of Multi-dimensional Perception Technology, Application and Cybersecurity NeurIPS 2023 [PUB] [SUPP] [PDF]
Federated Learning with Bilateral Curation for Partially Class-Disjoint Data SJTU; Shanghai AI Laboratory NeurIPS 2023 [PUB] [SUPP] [CODE]
Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds GMU; SJTU NeurIPS 2023 [PUB] [SUPP] [CODE]
FedL2P: Federated Learning to Personalize University of Cambridge; Samsung AI Center NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Adaptive Test-Time Personalization for Federated Learning UIUC NeurIPS 2023 [PUB] [PDF] [CODE]
Federated Conditional Stochastic Optimization University of Pittsburgh NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Federated Spectral Clustering via Secure Similarity Reconstruction CUHK NeurIPS 2023 [PUB]
Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM UM-Dearborn NeurIPS 2023 [PUB] [SUPP] [PDF]
FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks CMU NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Federated Multi-Objective Learning RIT NeurIPS 2023 [PUB] [SUPP] [PDF]
FLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout University of British Columbia; Gatech NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Resolving the Tug-of-War: A Separation of Communication and Learning in Federated Learning University of Pittsburgh NeurIPS 2023 [PUB] [SUPP]
Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems University of Pittsburgh NeurIPS 2023 [PUB] [SUPP] [PDF]
StableFDG: Style and Attention Based Learning for Federated Domain Generalization KAIST; Purdue University NeurIPS 2023 [PUB] [PDF]
Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization The University of Sydney NeurIPS 2023 [PUB] [SUPP] [PDF]
DELTA: Diverse Client Sampling for Fasting Federated Learning CUHK; The Shenzhen Institute of Artificial Intelligence and Robotics for Society NeurIPS 2023 [PUB] [SUPP] [PDF]
Federated Compositional Deep AUC Maximization Temple University NeurIPS 2023 [PUB] [SUPP] [PDF]
A3FL: Adversarially Adaptive Backdoor Attacks to Federated Learning PSU NeurIPS 2023 [PUB] [SUPP] [CODE]
Flow: Per-instance Personalized Federated Learning University of Massachusetts NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Eliminating Domain Bias for Federated Learning in Representation Space SJTU NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Federated Learning with Manifold Regularization and Normalized Update Reaggregation BIT NeurIPS 2023 [PUB] [SUPP] [PDF]
Structured Federated Learning through Clustered Additive Modeling University of Technology Sydney NeurIPS 2023 [PUB] [SUPP]
Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer ZJU; Singapore University of Technology and Design NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Dynamic Personalized Federated Learning with Adaptive Differential Privacy WHU NeurIPS 2023 [PUB] [SUPP] [CODE]
Fed-CO$_{2}$ : Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning ShanghaiTech University NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Solving a Class of Non-Convex Minimax Optimization in Federated Learning University of Pittsburgh NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Federated Learning via Meta-Variational Dropout SNU NeurIPS 2023 [PUB] [CODE]
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates Purdue University NeurIPS 2023 [PUB] [SUPP] [PDF]
SPACE: Single-round Participant Amalgamation for Contribution Evaluation in Federated Learning NTU NeurIPS 2023 [PUB] [CODE]
Fed-FA: Theoretically Modeling Client Data Divergence for Federated Language Backdoor Defense PKU; Tencent NeurIPS 2023 [PUB] [SUPP]
FedFed: Feature Distillation against Data Heterogeneity in Federated Learning BUAA; HKBU NeurIPS 2023 [PUB] [PDF] [CODE]
PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning SCU NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE] [解读]
Spectral Co-Distillation for Personalized Federated Learning SUTD NeurIPS 2023 [PUB]
Breaking the Communication-Privacy-Accuracy Tradeoff with $f$-Differential Privacy ZJU NeurIPS 2023 [PUB] [SUPP] [PDF]
Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation Stanford University NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
(Amplified) Banded Matrix Factorization: A unified approach to private training Google DeepMind NeurIPS 2023 [PUB] [SUPP] [PDF]
Aggregating Capacity in FL through Successive Layer Training for Computationally-Constrained Devices KIT NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation Stanford University NeurIPS 2023 [PUB] [SUPP] [PDF]
Incentivizing Honesty among Competitors in Collaborative Learning and Optimization ETH Zurich NeurIPS 2023 [PUB] [SUPP] [PDF]
Resilient Constrained Learning UPenn NeurIPS 2023 [PUB] [SUPP] [PDF]
A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting KAUST NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Collaboratively Learning Linear Models with Structured Missing Data Stanford University NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy EPFL NeurIPS 2023 [PUB] [SUPP] [PDF]
Fast Optimal Locally Private Mean Estimation via Random Projections Apple Inc. NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Contextual Stochastic Bilevel Optimization EPFL; ETH Zürich NeurIPS 2023 [PUB] [SUPP] [PDF]
Understanding Deep Gradient Leakage via Inversion Influence Functions MSU; Michigan State University; University of Texas at Austin NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Inner Product-based Neural Network Similarity Purdue University NeurIPS 2023 [PUB] [SUPP]
Correlation Aware Sparsified Mean Estimation Using Random Projection CMU NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
TIES-Merging: Resolving Interference When Merging Models UNC NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data Purdue University NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Large-Scale Distributed Learning via Private On-Device LSH UMD NeurIPS 2023 [PUB] [SUPP] [PDF]
Faster Relative Entropy Coding with Greedy Rejection Coding University of Cambridge NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization SJTU NeurIPS 2023 [PUB] [SUPP]
Momentum Provably Improves Error Feedback! ETH AI Center; ETH Zurich NeurIPS 2023 [PUB] [SUPP] [PDF]
Strategic Data Sharing between Competitors Sofia University NeurIPS 2023 [PUB] [SUPP] [PDF]
H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets GMU NeurIPS 2023 [PUB]
Wyze Rule: Federated Rule Dataset for Rule Recommendation Benchmarking Wyze Labs NeurIPS Datasets and Benchmarks 2023 [PUB] [SUPP] [DATASET]
Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning Google Research NeurIPS Datasets and Benchmarks 2023 [PUB] [PDF] [DATASET]
Text-driven Prompt Generation for Vision-Language Models in Federated Learning NeurIPS workshop 2023 [PUB]
HePCo: Data-Free Heterogeneous Prompt Consolidation for Continual Federated Learning NeurIPS workshop 2023 [PUB]
Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer Inputs of Language Models in Federated Learning NeurIPS workshop 2023 [PUB]
FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data NeurIPS workshop 2023 [PUB]
FedSoL: Bridging Global Alignment and Local Generality in Federated Learning NeurIPS workshop 2023 [PUB]
One-shot Empirical Privacy Estimation for Federated Learning NeurIPS workshop 2023 [PUB]
Profit: Benchmarking Personalization and Robustness Trade-off in Federated Prompt Tuning NeurIPS workshop 2023 [PUB]
SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models NeurIPS workshop 2023 [PUB]
The Fair Value of Data Under Heterogeneous Privacy Constraints in Federated Learning NeurIPS workshop 2023 [PUB]
Towards Building the FederatedGPT: Federated Instruction Tuning NeurIPS workshop 2023 [PUB]
Federated Learning for Speech Recognition: Revisiting Current Trends Towards Large-Scale ASR NeurIPS workshop 2023 [PUB]
LASER: Linear Compression in Wireless Distributed Optimization NeurIPS workshop 2023 [PUB]
MARINA Meets Matrix Stepsizes: Variance Reduced Distributed Non-Convex Optimization NeurIPS workshop 2023 [PUB]
TAMUNA: Doubly Accelerated Federated Learning with Local Training, Compression, and Partial Participation NeurIPS workshop 2023 [PUB]
An Empirical Evaluation of Federated Contextual Bandit Algorithms NeurIPS workshop 2023 [PUB]
RealFM: A Realistic Mechanism to Incentivize Data Contribution and Device Participation NeurIPS workshop 2023 [PUB]
FDAPT: Federated Domain-adaptive Pre-training for Language Models NeurIPS workshop 2023 [PUB]
Making Batch Normalization Great in Federated Deep Learning NeurIPS workshop 2023 [PUB]
Correlated Noise Provably Beats Independent Noise for Differentially Private Learning NeurIPS workshop 2023 [PUB]
Parameter Averaging Laws for Multitask Language Models NeurIPS workshop 2023 [PUB]
Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages NeurIPS workshop 2023 [PUB]
Beyond Parameter Averaging in Model Aggregation NeurIPS workshop 2023 [PUB]
Augmenting Federated Learning with Pretrained Transformers NeurIPS workshop 2023 [PUB]
Consensus Optimization at Representation: Improving Personalized Federated Learning via Data-Centric Regularization NeurIPS workshop 2023 [PUB]
DPZero: Dimension-Independent and Differentially Private Zeroth-Order Optimization NeurIPS workshop 2023 [PUB]
Leveraging Foundation Models to Improve Lightweight Clients in Federated Learning NeurIPS workshop 2023 [PUB]
FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System NeurIPS workshop 2023 [PUB]
Learning Optimizers for Local SGD NeurIPS workshop 2023 [PUB]
Exploring User-level Gradient Inversion with a Diffusion Prior NeurIPS workshop 2023 [PUB]
User Inference Attacks on Large Language Models NeurIPS workshop 2023 [PUB]
FedLDA: Personalized Federated Learning Through Collaborative Linear Discriminant Analysis NeurIPS workshop 2023 [PUB]
Heterogeneous LoRA for Federated Fine-tuning of On-device Foundation Models NeurIPS workshop 2023 [PUB]
Backdoor Threats from Compromised Foundation Models to Federated Learning NeurIPS workshop 2023 [PUB]
MOFL/D: A Federated Multi-objective Learning Framework with Decomposition NeurIPS workshop 2023 [PUB]
Absolute Variation Distance: an Inversion Attack Evaluation Metric for Federated Learning NeurIPS workshop 2023 [PUB]
Fed3R: Recursive Ridge Regression for Federated Learning with strong pre-trained models NeurIPS workshop 2023 [PUB]
FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning NeurIPS workshop 2023 [PUB]
Private and Personalized Histogram Estimation in a Federated Setting NeurIPS workshop 2023 [PUB]
The Aggregation–Heterogeneity Trade-off in Federated Learning PKU COLT 2023 [PUB]
FLASH: Automating federated learning using CASH Rensselaer Polytechnic Institute UAI 2023 [PUB] [SUPP] [MATERIAL]
Personalized federated domain adaptation for item-to-item recommendation AWS AI Labs UAI 2023 [PUB] [PDF] [SUPP] [MATERIAL] [CODE]
Fed-LAMB: Layer-wise and Dimension-wise Locally Adaptive Federated Learning Baidu Research UAI 2023 [PUB] [PDF] [SUPP] [MATERIAL]
Federated learning of models pre-trained on different features with consensus graphs IBM Research UAI 2023 [PUB] [SUPP] [MATERIAL] [CODE]
Fast Heterogeneous Federated Learning with Hybrid Client Selection NWPU UAI 2023 [PUB] [SUPP] [MATERIAL] [PDF]
Learning To Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning Cornell University UAI 2023 [PUB] [PDF] [SUPP] [MATERIAL] [CODE]
Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape The University of Sydney ICML 2023 [PUB] [PDF] [SLIDES]
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression: Fast Convergence and Partial Participation LinkedIn Ads ICML 2023 [PUB] [PDF]
FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization Alibaba Group ICML 2023 [PUB] [PDF] [CODE]
Federated Conformal Predictors for Distributed Uncertainty Quantification MIT ICML 2023 [PUB] [PDF] [CODE]
Federated Adversarial Learning: A Framework with Convergence Analysis UBC ICML 2023 [PUB] [PDF]
Federated Heavy Hitter Recovery under Linear Sketching Google Research ICML 2023 [PUB] [PDF] [CODE]
Doubly Adversarial Federated Bandits London School of Economics and Political Science ICML 2023 [PUB] [PDF] [CODE]
Achieving Linear Speedup in Non-IID Federated Bilevel Learning UC ICML 2023 [PUB] [PDF]
One-Shot Federated Conformal Prediction Université Paris-Saclay ICML 2023 [PUB] [PDF] [CODE]
Federated Online and Bandit Convex Optimization TTIC ICML 2023 [PUB]
Federated Linear Contextual Bandits with User-level Differential Privacy The Pennsylvania State University ICML 2023 [PUB] [PDF]
Vertical Federated Graph Neural Network for Recommender System NUS ICML 2023 [PUB] [PDF] [CODE]
Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation University at Buffalo ICML 2023 [PUB] [PDF]
Towards Understanding Ensemble Distillation in Federated Learning KAIST ICML 2023 [PUB]
Personalized Subgraph Federated Learning KAIST ICML 2023 [PUB] [PDF] [CODE]
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift Lagrange Mathematics and Computing Research Center; CMAP ICML 2023 [PUB] [PDF]
Secure Federated Correlation Test and Entropy Estimation CMU ICML 2023 [PUB] [PDF]
Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships JLU ICML 2023 [PUB] [CODE]
Personalized Federated Learning under Mixture of Distributions UCLA ICML 2023 [PUB] [PDF] [CODE]
FedDisco: Federated Learning with Discrepancy-Aware Collaboration SJTU ICML 2023 [PUB] [PDF] [CODE]
Anchor Sampling for Federated Learning with Partial Client Participation Purdue University ICML 2023 [PUB] [PDF] [CODE]
Private Federated Learning with Autotuned Compression JHU; Google ICML 2023 [PUB] [PDF]
Fast Federated Machine Unlearning with Nonlinear Functional Theory Auburn University ICML 2023 [PUB]
On the Convergence of Federated Averaging with Cyclic Client Participation CMU ICML 2023 [PUB] [PDF]
Revisiting Weighted Aggregation in Federated Learning with Neural Networks ZJU ICML 2023 [PUB] [PDF] [CODE]
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond CMU ICML 2023 [PUB] [PDF] [SLIDES]
GuardHFL: Privacy Guardian for Heterogeneous Federated Learning UESTC; NTU ICML 2023 [PUB]
Flash: Concept Drift Adaptation in Federated Learning University of Massachusetts ICML 2023 [PUB]
DoCoFL: Downlink Compression for Cross-Device Federated Learning VMware Research; Technion ICML 2023 [PUB] [PDF]
FeDXL: Provable Federated Learning for Deep X-Risk Optimization Texas A&M University ICML 2023 [PUB] [PDF] [CODE]
No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server Computation HIT ICML 2023 [PUB] [CODE]
Personalized Federated Learning with Inferred Collaboration Graphs SJTU ICML 2023 [PUB] [CODE]
Optimizing the Collaboration Structure in Cross-Silo Federated Learning UIUC ICML 2023 [PUB] [PDF] [CODE] [SLIDES]
TabLeak: Tabular Data Leakage in Federated Learning ETH Zurich ICML 2023 [PUB] [PDF] [CODE]
FedCR: Personalized Federated Learning Based on Across-Client Common Representation with Conditional Mutual Information Regularization SJTU ICML 2023 [PUB] [CODE]
Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction Duke University ICML 2023 [PUB] [PDF]
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design Meta AI ICML 2023 [PUB] [PDF] [CODE]
SRATTA: Sample Re-ATTribution Attack of Secure Aggregation in Federated Learning Owkin Inc. ICML 2023 [PUB] [PDF] [CODE]
Improving the Model Consistency of Decentralized Federated Learning THU ICML 2023 [PUB] [PDF]
Efficient Personalized Federated Learning via Sparse Model-Adaptation Alibaba Group ICML 2023 [PUB] [PDF] [CODE]
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning Univ. Lille ICML 2023 [PUB] [PDF] [CODE]
LeadFL: Client Self-Defense against Model Poisoning in Federated Learning TUD ICML 2023 [PUB] [CODE]
Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning HKUST ICML 2023 [PUB] [PDF] [CODE]
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models HKUST ICML 2023 [PUB] [PDF]
FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction CUHK; The Shenzhen Institute of Artificial Intelligence and Robotics for Society ICML 2023 [PUB] [PDF] [CODE]
Towards Unbiased Training in Federated Open-world Semi-supervised Learning PolyU ICML 2023 [PUB] [PDF] [SLIDES]
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning Using Independent Component Analysis Georgia Tech; Meta AI ICML 2023 [PUB] [PDF]
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning KU Leuven ICML 2023 [PUB] [PDF] [CODE]
Fair yet Asymptotically Equal Collaborative Learning NUS ICML 2023 [PUB] [PDF] [CODE]
Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability Adobe Research ICML 2023 [PUB] [PDF]
Adversarial Collaborative Learning on Non-IID Features UC Berkeley; NUS ICML 2023 [PUB]
XTab: Cross-table Pretraining for Tabular Transformers EPFL; Cornell University; AWS ICML 2023 [PUB] [PDF] [CODE]
Momentum Ensures Convergence of SIGNSGD under Weaker Assumptions NUDT ICML 2023 [PUB]
Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting Key Lab of Intelligent Computing Based Big Data of Zhejiang Province; ZJU; Sony Al ICML 2023 [PUB] [PDF] [CODE]
LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning Rensselaer Polytechnic Institute ICML 2023 [PUB] [PDF]
FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks University of Minnesota ICML 2023 [PUB]
Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm University of Chicago ICML 2023 [PUB] [PDF] [CODE]
Ensemble and continual federated learning for classification tasks. Universidade de Santiago de Compostela Mach Learn 2023 [PUB] [PDF]
FAC-fed: Federated adaptation for fairness and concept drift aware stream classification Leibniz University of Hannover Mach Learn 2023 [PUB]
Robust federated learning under statistical heterogeneity via hessian-weighted aggregation Deakin University Mach Learn 2023 [PUB]
FedLab: A Flexible Federated Learning Framework 🔥 UESTC; Peng Cheng Lab JMLR 2023 [PUB] [PDF] [CODE]
Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training? JMLR 2023 [PUB]
Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning TAMU JMLR 2023 [PUB] [PDF] [CODE]
A First Look into the Carbon Footprint of Federated Learning University of Cambridge JMLR 2023 [PUB] [PDF]
Attacks against Federated Learning Defense Systems and their Mitigation The University of Newcastle JMLR 2023 [PUB] [CODE]
A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates Universit ́e Cˆ ote d’Azur JMLR 2023 [PUB] [PDF] [CODE]
Tighter Regret Analysis and Optimization of Online Federated Learning Hanyang University TPAMI 2023 [PUB] [PDF]
Efficient Federated Learning Via Local Adaptive Amended Optimizer With Linear Speedup University of Sydney TPAMI 2023 [PDF]
Federated Learning Via Inexact ADMM. BJTU TPAMI 2023 [PUB] [PDF] [CODE]
FedIPR: Ownership Verification for Federated Deep Neural Network Models SJTU TPAMI 2023 [PUB] [PDF] [CODE] [解读]
Decentralized Federated Averaging NUDT TPAMI 2023 [PUB] [PDF]
Personalized Federated Learning with Feature Alignment and Classifier Collaboration THU ICLR 2023 [PUB] [CODE]
MocoSFL: enabling cross-client collaborative self-supervised learning ASU ICLR 2023 [PUB] [CODE]
Single-shot General Hyper-parameter Optimization for Federated Learning IBM ICLR 2023 [PUB] [PDF] [CODE]
Where to Begin? Exploring the Impact of Pre-Training and Initialization in Federated Facebook ICLR 2023 [PUB] [PDF] [CODE]
FedExP: Speeding up Federated Averaging via Extrapolation CMU ICLR 2023 [PUB] [PDF] [CODE]
Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection MSU ICLR 2023 [PUB] [CODE]
DASHA: Distributed Nonconvex Optimization with Communication Compression and Optimal Oracle Complexity KAUST ICLR 2023 [PUB] [PDF] [CODE]
Machine Unlearning of Federated Clusters University of Illinois ICLR 2023 [PUB] [PDF] [CODE]
Federated Neural Bandits NUS ICLR 2023 [PUB] [PDF] [CODE]
FedFA: Federated Feature Augmentation ETH Zurich ICLR 2023 [PUB] [PDF] [CODE]
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach CMU ICLR 2023 [PUB] [PDF] [CODE]
Better Generative Replay for Continual Federated Learning University of Virginia ICLR 2023 [PUB] [CODE]
Federated Learning from Small Datasets IKIM ICLR 2023 [PUB] [PDF]
Federated Nearest Neighbor Machine Translation USTC ICLR 2023 [PUB] [PDF]
Meta Knowledge Condensation for Federated Learning A*STAR ICLR 2023 [PUB] [PDF]
Test-Time Robust Personalization for Federated Learning EPFL ICLR 2023 [PUB] [PDF] [CODE]
DepthFL : Depthwise Federated Learning for Heterogeneous Clients SNU ICLR 2023 [PUB]
Towards Addressing Label Skews in One-Shot Federated Learning NUS ICLR 2023 [PUB] [CODE]
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning NUS ICLR 2023 [PUB] [PDF] [CODE]
Panning for Gold in Federated Learning: Targeted Text Extraction under Arbitrarily Large-Scale Aggregation UMD ICLR 2023 [PUB] [CODE]
SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication UMD ICLR 2023 [PUB] [PDF] [CODE]
Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses USC ICLR 2023 [PUB] [PDF] [CODE]
Effective passive membership inference attacks in federated learning against overparameterized models Purdue University ICLR 2023 [PUB]
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification University of Cambridge ICLR 2023 [PUB] [PDF] [CODE]
Multimodal Federated Learning via Contrastive Representation Ensemble THU ICLR 2023 [PUB] [PDF] [CODE]
Faster federated optimization under second-order similarity Princeton University ICLR 2023 [PUB] [PDF] [CODE]
FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy University of Sydney ICLR 2023 [PUB] [CODE]
The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation utexas ICLR 2023 [PUB] [PDF] [CODE]
PerFedMask: Personalized Federated Learning with Optimized Masking Vectors UBC ICLR 2023 [PUB] [CODE]
EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data GMU ICLR 2023 [PUB] [CODE]
FedDAR: Federated Domain-Aware Representation Learning Harvard ICLR 2023 [PUB] [PDF] [CODE]
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning upenn ICLR 2023 [PUB] [CODE]
FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning Purdue University ICLR 2023 [PUB] [PDF] [CODE]
Generalization Bounds for Federated Learning: Fast Rates, Unparticipating Clients and Unbounded Losses RUC ICLR 2023 [PUB]
Efficient Federated Domain Translation Purdue University ICLR 2023 [PUB] [CODE]
On the Importance and Applicability of Pre-Training for Federated Learning OSU ICLR 2023 [PUB] [PDF] [CODE]
Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models UMD ICLR 2023 [PUB] [PDF] [CODE]
A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy UCLA ICLR 2023 [PUB] [PDF]
Instance-wise Batch Label Restoration via Gradients in Federated Learning BUAA ICLR 2023 [PUB] [CODE]
Data-Free One-Shot Federated Learning Under Very High Statistical Heterogeneity College of William and Mary ICLR 2023 [PUB]
CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning University of Warwick ICLR 2023 [PUB] [PDF] [CODE]
Sparse Random Networks for Communication-Efficient Federated Learning Stanford ICLR 2023 [PUB] [PDF] [CODE]
Combating Exacerbated Heterogeneity for Robust Decentralized Models HKBU ICLR 2023 [PUB] [CODE]
Hyperparameter Optimization through Neural Network Partitioning University of Cambridge ICLR 2023 [PUB] [PDF]
Does Decentralized Learning with Non-IID Unlabeled Data Benefit from Self Supervision? MIT ICLR 2023 [PUB] [PDF] [CODE]
Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top mbzuai ICLR 2023 [PUB] [PDF] [CODE]
Dual Diffusion Implicit Bridges for Image-to-Image Translation Stanford ICLR 2023 [PUB] [PDF] [CODE]
An accurate, scalable and verifiable protocol for federated differentially private averaging INRIA Lille Mach Learn 2022 [PUB] [PDF]
Federated online clustering of bandits. CUHK UAI 2022 [PUB] [PDF] [CODE]
Privacy-aware compression for federated data analysis. Meta AI UAI 2022 [PUB] [PDF] [CODE]
Faster non-convex federated learning via global and local momentum. UTEXAS UAI 2022 [PUB] [PDF]
Fedvarp: Tackling the variance due to partial client participation in federated learning. CMU UAI 2022 [PUB] [PDF]
SASH: Efficient secure aggregation based on SHPRG for federated learning CAS; CASTEST UAI 2022 [PUB] [PDF]
Bayesian federated estimation of causal effects from observational data NUS UAI 2022 [PUB] [PDF]
Communication-Efficient Randomized Algorithm for Multi-Kernel Online Federated Learning Hanyang University TPAMI 2022 [PUB]
Lazily Aggregated Quantized Gradient Innovation for Communication-Efficient Federated Learning ZJU TPAMI 2022 [PUB] [CODE]
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox Moscow Institute of Physics and Technology NeurIPS 2022 [PUB] [PDF]
LAMP: Extracting Text from Gradients with Language Model Priors ETHZ NeurIPS 2022 [PUB] [CODE]
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning utexas NeurIPS 2022 [PUB] [PDF]
On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond NUIST NeurIPS 2022 [PUB] [PDF]
Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams WISC NeurIPS 2022 [PUB] [CODE]
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks Columbia University NeurIPS 2022 [PUB] [PDF]
Asymptotic Behaviors of Projected Stochastic Approximation: A Jump Diffusion Perspective PKU NeurIPS 2022 [PUB]
Subspace Recovery from Heterogeneous Data with Non-isotropic Noise Stanford NeurIPS 2022 [PUB] [PDF]
EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization KAUST NeurIPS 2022 [PUB] [PDF]
On-Demand Sampling: Learning Optimally from Multiple Distributions UC Berkeley NeurIPS 2022 [PUB] [CODE]
Improved Utility Analysis of Private CountSketch ITU NeurIPS 2022 [PUB] [PDF] [CODE]
Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning HUAWEI NeurIPS 2022 [PUB] [CODE]
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities phystech NeurIPS 2022 [PUB] [PDF]
BEER: Fast O(1/T) Rate for Decentralized Nonconvex Optimization with Communication Compression Princeton NeurIPS 2022 [PUB] [PDF] [CODE]
Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning The University of Tokyo NeurIPS 2022 [PUB] [PDF]
Near-Optimal Collaborative Learning in Bandits INRIA; Inserm NeurIPS 2022 [PUB] [PDF] [CODE]
Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees phystech NeurIPS 2022 [PUB] [PDF]
Towards Optimal Communication Complexity in Distributed Non-Convex Optimization TTIC NeurIPS 2022 [PUB] [CODE]
FedPop: A Bayesian Approach for Personalised Federated Learning Skoltech NeurIPS 2022 [PUB] [PDF]
Fairness in Federated Learning via Core-Stability UIUC NeurIPS 2022 [PUB] [CODE]
SecureFedYJ: a safe feature Gaussianization protocol for Federated Learning Sorbonne Université NeurIPS 2022 [PUB] [PDF]
FedRolex: Model-Heterogeneous Federated Learning with Rolling Submodel Extraction MSU NeurIPS 2022 [PUB] [CODE]
On Sample Optimality in Personalized Collaborative and Federated Learning INRIA NeurIPS 2022 [PUB]
DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing HKUST NeurIPS 2022 [PUB] [PDF]
FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning THU NeurIPS 2022 [PUB]
Variance Reduced ProxSkip: Algorithm, Theory and Application to Federated Learning KAUST NeurIPS 2022 [PUB] [PDF]
VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? WHU NeurIPS 2022 [PUB] [CODE]
DENSE: Data-Free One-Shot Federated Learning ZJU NeurIPS 2022 [PUB] [PDF]
CalFAT: Calibrated Federated Adversarial Training with Label Skewness ZJU NeurIPS 2022 [PUB] [PDF]
SAGDA: Achieving O(ϵ−2) Communication Complexity in Federated Min-Max Learning OSU NeurIPS 2022 [PUB] [PDF]
Taming Fat-Tailed (“Heavier-Tailed” with Potentially Infinite Variance) Noise in Federated Learning OSU NeurIPS 2022 [PUB] [PDF]
Personalized Federated Learning towards Communication Efficiency, Robustness and Fairness PKU NeurIPS 2022 [PUB]
Federated Submodel Optimization for Hot and Cold Data Features SJTU NeurIPS 2022 [PUB]
BooNTK: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels UC Berkeley NeurIPS 2022 [PUB] [PDF]
Byzantine-tolerant federated Gaussian process regression for streaming data PSU NeurIPS 2022 [PUB] [CODE]
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression CMU NeurIPS 2022 [PUB] [PDF]
Coresets for Vertical Federated Learning: Regularized Linear Regression and K-Means Clustering Yale NeurIPS 2022 [PUB] [PDF] [CODE]
Communication Efficient Federated Learning for Generalized Linear Bandits University of Virginia NeurIPS 2022 [PUB] [CODE]
Recovering Private Text in Federated Learning of Language Models Princeton NeurIPS 2022 [PUB] [PDF] [CODE]
Federated Learning from Pre-Trained Models: A Contrastive Learning Approach UTS NeurIPS 2022 [PUB] [PDF]
Global Convergence of Federated Learning for Mixed Regression Northeastern University NeurIPS 2022 [PUB] [PDF]
Resource-Adaptive Federated Learning with All-In-One Neural Composition JHU NeurIPS 2022 [PUB]
Self-Aware Personalized Federated Learning Amazon NeurIPS 2022 [PUB] [PDF]
A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning Northeastern University NeurIPS 2022 [PUB] [PDF]
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects NUS NeurIPS 2022 [PUB]
Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning EPFL NeurIPS 2022 [PUB] [PDF]
Personalized Online Federated Multi-Kernel Learning UCI NeurIPS 2022 [PUB]
SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training Duke University NeurIPS 2022 [PUB] [PDF] [CODE]
A Unified Analysis of Federated Learning with Arbitrary Client Participation IBM NeurIPS 2022 [PUB] [PDF]
Preservation of the Global Knowledge by Not-True Distillation in Federated Learning KAIST NeurIPS 2022 [PUB] [PDF] [CODE]
FedSR: A Simple and Effective Domain Generalization Method for Federated Learning University of Oxford NeurIPS 2022 [PUB] [CODE]
Factorized-FL: Personalized Federated Learning with Parameter Factorization & Similarity Matching KAIST NeurIPS 2022 [PUB] [PDF] [CODE]
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits UC NeurIPS 2022 [PUB] [PDF]
Learning to Attack Federated Learning: A Model-based Reinforcement Learning Attack Framework Tulane University NeurIPS 2022 [PUB]
On Privacy and Personalization in Cross-Silo Federated Learning CMU NeurIPS 2022 [PUB] [PDF]
A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning NUS NeurIPS 2022 [PUB] [PDF] [CODE]
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings Owkin NeurIPS Datasets and Benchmarks 2022 [PUB] [CODE]
A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources University of Pittsburgh ICML 2022 [PUB] [PDF] [CODE]
Fast Composite Optimization and Statistical Recovery in Federated Learning SJTU ICML 2022 [PUB] [PDF] [CODE]
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning NYU ICML 2022 [PUB] [PDF] [CODE]
The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning 🔥 Stanford; Google Research ICML 2022 [PUB] [PDF] [CODE] [SLIDE]
The Poisson Binomial Mechanism for Unbiased Federated Learning with Secure Aggregation Stanford; Google Research ICML 2022 [PUB] [PDF] [CODE]
DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training USTC ICML 2022 [PUB] [PDF] [CODE]
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning University of Oulu ICML 2022 [PUB] [PDF] [CODE]
DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning University of Cambridge ICML 2022 [PUB] [PDF] [SLIDE] [CODE]
Accelerated Federated Learning with Decoupled Adaptive Optimization Auburn University ICML 2022 [PUB] [PDF]
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling Georgia Tech ICML 2022 [PUB] [PDF]
Multi-Level Branched Regularization for Federated Learning Seoul National University ICML 2022 [PUB] [PDF] [CODE] [PAGE]
FedScale: Benchmarking Model and System Performance of Federated Learning at Scale 🔥 University of Michigan ICML 2022 [PUB] [PDF] [CODE]
Federated Learning with Positive and Unlabeled Data XJTU ICML 2022 [PUB] [PDF] [CODE]
Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning SJTU ICML 2022 [PUB] [CODE]
Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering University of Michigan ICML 2022 [PUB] [PDF] [CODE]
Disentangled Federated Learning for Tackling Attributes Skew via Invariant Aggregation and Diversity Transferring USTC ICML 2022 [PUB] [PDF] [CODE] [SLIDE] [解读]
Architecture Agnostic Federated Learning for Neural Networks The University of Texas at Austin ICML 2022 [PUB] [PDF] [SLIDE]
Personalized Federated Learning through Local Memorization Inria ICML 2022 [PUB] [PDF] [CODE]
Proximal and Federated Random Reshuffling KAUST ICML 2022 [PUB] [PDF] [CODE]
Federated Learning with Partial Model Personalization University of Washington ICML 2022 [PUB] [PDF] [CODE]
Generalized Federated Learning via Sharpness Aware Minimization University of South Florida ICML 2022 [PUB] [PDF]
FedNL: Making Newton-Type Methods Applicable to Federated Learning KAUST ICML 2022 [PUB] [PDF] [VIDEO] [SLIDE]
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms CMU ICML 2022 [PUB] [PDF] [SLIDE]
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning Hong Kong Baptist University ICML 2022 [PUB] [PDF] [CODE] [解读]
FedNest: Federated Bilevel, Minimax, and Compositional Optimization University of Michigan ICML 2022 [PUB] [PDF] [CODE]
EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning VMware Research ICML 2022 [PUB] [PDF] [CODE]
Communication-Efficient Adaptive Federated Learning Pennsylvania State University ICML 2022 [PUB] [PDF]
ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training CISPA Helmholz Center for Information Security ICML 2022 [PUB] [PDF] [SLIDE] [CODE]
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification 🔥 University of Maryland ICML 2022 [PUB] [PDF] [CODE]
Anarchic Federated Learning The Ohio State University ICML 2022 [PUB] [PDF]
QSFL: A Two-Level Uplink Communication Optimization Framework for Federated Learning Nankai University ICML 2022 [PUB] [CODE]
Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization KAIST ICML 2022 [PUB] [PDF]
Neural Tangent Kernel Empowered Federated Learning NC State University ICML 2022 [PUB] [PDF] [CODE]
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy UMN ICML 2022 [PUB] [PDF]
Personalized Federated Learning via Variational Bayesian Inference CAS ICML 2022 [PUB] [PDF] [SLIDE] [UC.]
Federated Learning with Label Distribution Skew via Logits Calibration ZJU ICML 2022 [PUB]
Neurotoxin: Durable Backdoors in Federated Learning Southeast University;Princeton ICML 2022 [PUB] [PDF] [CODE]
Resilient and Communication Efficient Learning for Heterogeneous Federated Systems Michigan State University ICML 2022 [PUB]
Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond KAIST ICLR (oral) 2022 [PUB] [CODE]
Bayesian Framework for Gradient Leakage ETH Zurich ICLR 2022 [PUB] [PDF] [CODE]
Federated Learning from only unlabeled data with class-conditional-sharing clients The University of Tokyo; CUHK ICLR 2022 [PUB] [CODE]
FedChain: Chained Algorithms for Near-Optimal Communication Cost in Federated Learning CMU; University of Illinois at Urbana-Champaign; University of Washington ICLR 2022 [PUB] [PDF]
Acceleration of Federated Learning with Alleviated Forgetting in Local Training THU ICLR 2022 [PUB] [PDF] [CODE]
FedPara: Low-rank Hadamard Product for Communicatkion-Efficient Federated Learning POSTECH ICLR 2022 [PUB] [PDF] [CODE]
An Agnostic Approach to Federated Learning with Class Imbalance University of Pennsylvania ICLR 2022 [PUB] [CODE]
Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization Michigan State University; The University of Texas at Austin ICLR 2022 [PUB] [PDF] [CODE]
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models 🔥 University of Maryland; NYU ICLR 2022 [PUB] [PDF] [CODE]
ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity University of Cambridge; University of Oxford ICLR 2022 [PUB] [PDF]
Diverse Client Selection for Federated Learning via Submodular Maximization Intel; CMU ICLR 2022 [PUB] [CODE]
Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank? Purdue ICLR 2022 [PUB] [PDF] [CODE]
Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions 🔥 University of Maryland; Google ICLR 2022 [PUB] [CODE]
Towards Model Agnostic Federated Learning Using Knowledge Distillation EPFL ICLR 2022 [PUB] [PDF] [CODE]
Divergence-aware Federated Self-Supervised Learning NTU; SenseTime ICLR 2022 [PUB] [PDF] [CODE]
What Do We Mean by Generalization in Federated Learning? 🔥 Stanford; Google ICLR 2022 [PUB] [PDF] [CODE]
FedBABU: Toward Enhanced Representation for Federated Image Classification KAIST ICLR 2022 [PUB] [PDF] [CODE]
Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing EPFL ICLR 2022 [PUB] [PDF] [CODE]
Improving Federated Learning Face Recognition via Privacy-Agnostic Clusters Aibee ICLR Spotlight 2022 [PUB] [PDF] [PAGE] [解读]
Hybrid Local SGD for Federated Learning with Heterogeneous Communications University of Texas; Pennsylvania State University ICLR 2022 [PUB]
On Bridging Generic and Personalized Federated Learning for Image Classification The Ohio State University ICLR 2022 [PUB] [PDF] [CODE]
Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond KAIST; MIT ICLR 2022 [PUB] [PDF]
One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them. JMLR 2021 [PUB] [CODE]
Constrained differentially private federated learning for low-bandwidth devices UAI 2021 [PUB] [PDF]
Federated stochastic gradient Langevin dynamics UAI 2021 [PUB] [PDF]
Federated Learning Based on Dynamic Regularization BU; ARM ICLR 2021 [PUB] [PDF] [CODE]
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning The Ohio State University ICLR 2021 [PUB] [PDF]
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients Duke University ICLR 2021 [PUB] [PDF] [CODE]
FedMix: Approximation of Mixup under Mean Augmented Federated Learning KAIST ICLR 2021 [PUB] [PDF]
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms 🔥 CMU; Google ICLR 2021 [PUB] [PDF] [CODE]
Adaptive Federated Optimization 🔥 Google ICLR 2021 [PUB] [PDF] [CODE]
Personalized Federated Learning with First Order Model Optimization Stanford; NVIDIA ICLR 2021 [PUB] [PDF] [CODE] [UC.]
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization 🔥 Princeton ICLR 2021 [PUB] [PDF] [CODE]
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning The Ohio State University ICLR 2021 [PUB] [PDF] [CODE]
Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning KAIST ICLR 2021 [PUB] [PDF] [CODE]
KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation ZJU ICML 2021 [PUB] [PDF] [CODE] [解读]
Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix Harvard University ICML 2021 [PUB] [PDF] [VIDEO] [CODE]
FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis PKU; Princeton ICML 2021 [PUB] [PDF] [VIDEO]
Personalized Federated Learning using Hypernetworks 🔥 Bar-Ilan University; NVIDIA ICML 2021 [PUB] [PDF] [CODE] [PAGE] [VIDEO] [解读]
Federated Composite Optimization Stanford; Google ICML 2021 [PUB] [PDF] [CODE] [VIDEO] [SLIDE]
Exploiting Shared Representations for Personalized Federated Learning University of Texas at Austin; University of Pennsylvania ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Data-Free Knowledge Distillation for Heterogeneous Federated Learning 🔥 Michigan State University ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Federated Continual Learning with Weighted Inter-client Transfer KAIST ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity The University of Iowa ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning The University of Tokyo ICML 2021 [PUB] [PDF] [VIDEO]
Federated Learning of User Verification Models Without Sharing Embeddings Qualcomm ICML 2021 [PUB] [PDF] [VIDEO]
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning Accenture ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Ditto: Fair and Robust Federated Learning Through Personalization CMU; Facebook AI ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Heterogeneity for the Win: One-Shot Federated Clustering CMU ICML 2021 [PUB] [PDF] [VIDEO]
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation 🔥 Google ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Debiasing Model Updates for Improving Personalized Federated Training BU; Arm ICML 2021 [PUB] [CODE] [VIDEO]
One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning Toyota; Berkeley; Cornell University ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks UIUC; IBM ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Federated Learning under Arbitrary Communication Patterns Indiana University; Amazon ICML 2021 [PUB] [VIDEO]
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression CMU NeurIPS 2021 [PUB] [PDF]
Boosting with Multiple Sources Google NeurIPS 2021 [PUB]
DRIVE: One-bit Distributed Mean Estimation VMware NeurIPS 2021 [PUB] [CODE]
Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning NUS NeurIPS 2021 [PUB] [CODE]
Gradient Inversion with Generative Image Prior POSTECH NeurIPS 2021 [PUB] [PDF] [CODE]
Distributed Machine Learning with Sparse Heterogeneous Data University of Oxford NeurIPS 2021 [PUB] [PDF]
Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning UCLA NeurIPS 2021 [PUB] [PDF]
Sageflow: Robust Federated Learning against Both Stragglers and Adversaries KAIST NeurIPS 2021 [PUB]
CAFE: Catastrophic Data Leakage in Vertical Federated Learning Rensselaer Polytechnic Institute; IBM Research NeurIPS 2021 [PUB] [CODE]
Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee NUS NeurIPS 2021 [PUB] [PDF] [CODE]
Optimality and Stability in Federated Learning: A Game-theoretic Approach Cornell University NeurIPS 2021 [PUB] [PDF] [CODE]
QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning UCLA NeurIPS 2021 [PUB] [PDF] [CODE] [解读]
The Skellam Mechanism for Differentially Private Federated Learning 🔥 Google Research; CMU NeurIPS 2021 [PUB] [PDF] [CODE]
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data NUS; Huawei NeurIPS 2021 [PUB] [PDF]
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning UMN NeurIPS 2021 [PUB] [PDF]
Subgraph Federated Learning with Missing Neighbor Generation Emory; UBC; Lehigh University NeurIPS 2021 [PUB] [PDF] [CODE] [解读]
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning 🔥 Princeton NeurIPS 2021 [PUB] [PDF] [CODE]
Personalized Federated Learning With Gaussian Processes Bar-Ilan University NeurIPS 2021 [PUB] [PDF] [CODE]
Differentially Private Federated Bayesian Optimization with Distributed Exploration MIT; NUS NeurIPS 2021 [PUB] [PDF] [CODE]
Parameterized Knowledge Transfer for Personalized Federated Learning PolyU NeurIPS 2021 [PUB] [PDF] [CODE]
Federated Reconstruction: Partially Local Federated Learning 🔥 Google Research NeurIPS 2021 [PUB] [PDF] [CODE] [UC.]
Fast Federated Learning in the Presence of Arbitrary Device Unavailability THU; Princeton; MIT NeurIPS 2021 [PUB] [PDF] [CODE]
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective Duke University; Accenture Labs NeurIPS 2021 [PUB] [PDF] [CODE]
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout KAUST; Samsung AI Center NeurIPS 2021 [PUB] [PDF]
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients University of Pennsylvania NeurIPS 2021 [PUB] [PDF] [VIDEO]
Federated Multi-Task Learning under a Mixture of Distributions INRIA; Accenture Labs NeurIPS 2021 [PUB] [PDF] [CODE]
Federated Graph Classification over Non-IID Graphs Emory NeurIPS 2021 [PUB] [PDF] [CODE] [解读]
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing CMU; Hewlett Packard Enterprise NeurIPS 2021 [PUB] [PDF] [CODE]
On Large-Cohort Training for Federated Learning 🔥 Google; CMU NeurIPS 2021 [PUB] [PDF] [CODE]
DeepReduce: A Sparse-tensor Communication Framework for Federated Deep Learning KAUST; Columbia University; University of Central Florida NeurIPS 2021 [PUB] [PDF] [CODE]
PartialFed: Cross-Domain Personalized Federated Learning via Partial Initialization Huawei NeurIPS 2021 [PUB] [VIDEO]
Federated Split Task-Agnostic Vision Transformer for COVID-19 CXR Diagnosis KAIST NeurIPS 2021 [PUB] [PDF]
Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning THU; Alibaba; Weill Cornell Medicine NeurIPS 2021 [PUB] [PDF] [CODE]
Federated Linear Contextual Bandits The Pennsylvania State University; Facebook; University of Virginia NeurIPS 2021 [PUB] [PDF] [CODE]
Few-Round Learning for Federated Learning KAIST NeurIPS 2021 [PUB]
Breaking the centralized barrier for cross-device federated learning EPFL; Google Research NeurIPS 2021 [PUB] [CODE] [VIDEO]
Federated-EM with heterogeneity mitigation and variance reduction Ecole Polytechnique; Google Research NeurIPS 2021 [PUB] [PDF]
Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning MIT; Amazon; Google NeurIPS 2021 [PUB] [PAGE] [SLIDE]
FedDR – Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization University of North Carolina at Chapel Hill; IBM Research NeurIPS 2021 [PUB] [PDF] [CODE]
Federated Adversarial Domain Adaptation BU; Columbia University; Rutgers University ICLR 2020 [PUB] [PDF] [CODE]
DBA: Distributed Backdoor Attacks against Federated Learning ZJU; IBM Research ICLR 2020 [PUB] [CODE]
Fair Resource Allocation in Federated Learning 🔥 CMU; Facebook AI ICLR 2020 [PUB] [PDF] [CODE]
Federated Learning with Matched Averaging 🔥 University of Wisconsin-Madison; IBM Research ICLR 2020 [PUB] [PDF] [CODE]
Differentially Private Meta-Learning CMU ICLR 2020 [PUB] [PDF]
Generative Models for Effective ML on Private, Decentralized Datasets 🔥 Google ICLR 2020 [PUB] [PDF] [CODE]
On the Convergence of FedAvg on Non-IID Data 🔥 PKU ICLR 2020 [PUB] [PDF] [CODE] [解读]
FedBoost: A Communication-Efficient Algorithm for Federated Learning Google ICML 2020 [PUB] [VIDEO]
FetchSGD: Communication-Efficient Federated Learning with Sketching UC Berkeley; Johns Hopkins University; Amazon ICML 2020 [PUB] [PDF] [VIDEO] [CODE]
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning EPFL; Google ICML 2020 [PUB] [PDF] [VIDEO] [UC.] [解读]
Federated Learning with Only Positive Labels Google ICML 2020 [PUB] [PDF] [VIDEO]
From Local SGD to Local Fixed-Point Methods for Federated Learning Moscow Institute of Physics and Technology; KAUST ICML 2020 [PUB] [PDF] [SLIDE] [VIDEO]
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization KAUST ICML 2020 [PUB] [PDF] [SLIDE] [VIDEO]
Differentially-Private Federated Linear Bandits MIT NeurIPS 2020 [PUB] [PDF] [CODE]
Federated Principal Component Analysis University of Cambridge; Quine Technologies NeurIPS 2020 [PUB] [PDF] [CODE]
FedSplit: an algorithmic framework for fast federated optimization UC Berkeley NeurIPS 2020 [PUB] [PDF]
Federated Bayesian Optimization via Thompson Sampling NUS; MIT NeurIPS 2020 [PUB] [PDF] [CODE]
Lower Bounds and Optimal Algorithms for Personalized Federated Learning KAUST NeurIPS 2020 [PUB] [PDF]
Robust Federated Learning: The Case of Affine Distribution Shifts UC Santa Barbara; MIT NeurIPS 2020 [PUB] [PDF] [CODE]
An Efficient Framework for Clustered Federated Learning UC Berkeley; DeepMind NeurIPS 2020 [PUB] [PDF] [CODE]
Distributionally Robust Federated Averaging 🔥 Pennsylvania State University NeurIPS 2020 [PUB] [PDF] [CODE]
Personalized Federated Learning with Moreau Envelopes 🔥 The University of Sydney NeurIPS 2020 [PUB] [PDF] [CODE]
Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach MIT; UT Austin NeurIPS 2020 [PUB] [PDF] [UC.]
Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge USC NeurIPS 2020 [PUB] [PDF] [CODE] [解读]
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization 🔥 CMU; Princeton NeurIPS 2020 [PUB] [PDF] [CODE] [UC.]
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning University of Wisconsin-Madison NeurIPS 2020 [PUB] [PDF]
Federated Accelerated Stochastic Gradient Descent Stanford NeurIPS 2020 [PUB] [PDF] [CODE] [VIDEO]
Inverting Gradients - How easy is it to break privacy in federated learning? 🔥 University of Siegen NeurIPS 2020 [PUB] [PDF] [CODE]
Ensemble Distillation for Robust Model Fusion in Federated Learning EPFL NeurIPS 2020 [PUB] [PDF] [CODE]
Throughput-Optimal Topology Design for Cross-Silo Federated Learning INRIA NeurIPS 2020 [PUB] [PDF] [CODE]
Bayesian Nonparametric Federated Learning of Neural Networks 🔥 IBM ICML 2019 [PUB] [PDF] [CODE]
Analyzing Federated Learning through an Adversarial Lens 🔥 Princeton; IBM ICML 2019 [PUB] [PDF] [CODE]
Agnostic Federated Learning Google ICML 2019 [PUB] [PDF]
cpSGD: Communication-efficient and differentially-private distributed SGD Princeton; Google NeurIPS 2018 [PUB] [PDF]
Federated Multi-Task Learning 🔥 Stanford; USC; CMU NeurIPS 2017 [PUB] [PDF] [CODE]

fl in top dm conference and journal

Federated Learning papers accepted by top DM(Data Mining) conference and journal, Including KDD(ACM SIGKDD Conference on Knowledge Discovery and Data Mining) and WSDM(Web Search and Data Mining).

fl in top dm conference and journal
Title Affiliation Venue Year Materials
FedKDD: International Joint Workshop on Federated Learning for Data Mining and Graph Analytics KDD Workshop 2024 [PUB]
Is Aggregation the Only Choice? Federated Learning via Layer-wise Model Recombination KDD 2024 [PUB]
BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning KDD 2024 [PUB]
Federated Graph Learning with Structure Proxy Alignment KDD 2024 [PUB]
HiFGL: A Hierarchical Framework for Cross-silo Cross-device Federated Graph Learning KDD 2024 [PUB]
FedSecurity: A Benchmark for Attacks and Defenses in Federated Learning and Federated LLMs KDD 2024 [PUB]
Distributed Harmonization: Federated Clustered Batch Effect Adjustment and Generalization KDD 2024 [PUB]
FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning KDD 2024 [PUB]
On the Convergence of Zeroth-Order Federated Tuning for Large Language Models KDD 2024 [PUB]
CASA: Clustered Federated Learning with Asynchronous Clients KDD 2024 [PUB]
FLAIM: AIM-based Synthetic Data Generation in the Federated Setting KDD 2024 [PUB]
Privacy-Preserving Federated Learning using Flower Framework KDD 2024 [PUB]
FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning KDD 2024 [PUB]
FedNLR: Federated Learning with Neuron-wise Learning Rates KDD 2024 [PUB]
FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model KDD 2024 [PUB]
FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation KDD 2024 [PUB]
Preventing Strategic Behaviors in Collaborative Inference for Vertical Federated Learning KDD 2024 [PUB]
PeFAD: A Parameter-Efficient Federated Framework for Time Series Anomaly Detection KDD 2024 [PUB]
FedRoLA: Robust Federated Learning Against Model Poisoning via Layer-based Aggregation KDD 2024 [PUB]
FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction KDD 2024 [PUB]
OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learning KDD 2024 [PUB]
Personalized Federated Continual Learning via Multi-Granularity Prompt KDD 2024 [PUB]
Enabling Collaborative Test-Time Adaptation in Dynamic Environment via Federated Learning KDD 2024 [PUB]
GPFedRec: Graph-Guided Personalization for Federated Recommendation KDD 2024 [PUB]
Asynchronous Vertical Federated Learning for Kernelized AUC Maximization KDD 2024 [PUB]
VertiMRF: Differentially Private Vertical Federated Data Synthesis KDD 2024 [PUB]
User Consented Federated Recommender System Against Personalized Attribute Inference Attack HKUST WSDM 2024 [PUB] [PDF] [CODE]
Guardian: Guarding against Gradient Leakage with Provable Defense for Federated Learning ECNU WSDM 2024 [PUB]
Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation University of Cambridge KDD 2023 [PUB] [PDF]
FedDefender: Client-Side Attack-Tolerant Federated Learning KAIST KDD 2023 [PUB] [PDF] [CODE]
FedAPEN: Personalized Cross-silo Federated Learning with Adaptability to Statistical Heterogeneity ZJU KDD 2023 [PUB] [CODE]
FedPseudo: Privacy-Preserving Pseudo Value-Based Deep Learning Models for Federated Survival Analysis UMBC KDD 2023 [PUB] [PDF]
ShapleyFL: Robust Federated Learning Based on Shapley Value ZJU KDD 2023 [PUB] [CODE]
Federated Few-shot Learning University of Virginia KDD 2023 [PUB] [PDF] [CODE]
Theoretical Convergence Guaranteed Resource-Adaptive Federated Learning with Mixed Heterogeneity SDU KDD 2023 [PUB]
Personalized Federated Learning with Parameter Propagation UIUC KDD 2023 [PUB]
Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining University of Pittsburgh KDD 2023 [PUB] [PDF] [CODE]
CriticalFL: A Critical Learning Periods Augmented Client Selection Framework for Efficient Federated Learning SUNY-Binghamton University KDD 2023 [PUB] [PDF]
FLAMES2Graph: An Interpretable Federated Multivariate Time Series Classification Framework L3S Research Center KDD 2023 [PUB] [PDF]
FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy SJTU KDD 2023 [PUB] [PDF] [CODE]
Navigating Alignment for Non-identical Client Class Sets: A Label Name-Anchored Federated Learning Framework UCSD KDD 2023 [PUB] [PDF] [CODE]
DM-PFL: Hitchhiking Generic Federated Learning for Efficient Shift-Robust Personalization BUAA KDD 2023 [PUB] [CODE]
FS-REAL: Towards Real-World Cross-Device Federated Learning Alibaba Group KDD 2023 [PUB] [PDF]
FedMultimodal: A Benchmark for Multimodal Federated Learning USC KDD 2023 [PUB] [PDF] [CODE]
PrivateRec: Differentially Private Model Training and Online Serving for Federated News Recommendation RUC KDD 2023 [PUB] [PDF] [NEWS]
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks HKUST; Alibaba Group KDD 2023 [PUB] [PDF] [CODE]
UA-FedRec: Untargeted Attack on Federated News Recommendation USTC KDD 2023 [PUB] [PDF] [CODE]
International Workshop on Federated Learning for Distributed Data Mining MSU KDD Workshop Summaries 2023 [PUB] [PAGE]
Is Normalization Indispensable for Multi-domain Federated Learning? KDD workshop 2023 [PUB]
Distributed Personalized Empirical Risk Minimization. KDD workshop 2023 [PUB]
Once-for-All Federated Learning: Learning From and Deploying to Heterogeneous Clients. KDD workshop 2023 [PUB]
SparseVFL: Communication-Efficient Vertical Federated Learning Based on Sparsification of Embeddings and Gradients. KDD workshop 2023 [PUB]
Optimization of User Resources in Federated Learning for Urban Sensing Applications KDD workshop 2023 [PUB]
FedLEGO: Enabling Heterogenous Model Cooperation via Brick Reassembly in Federated Learning. KDD workshop 2023 [PUB]
Federated Graph Analytics with Differential Privacy. KDD workshop 2023 [PUB]
Scaling Distributed Multi-task Reinforcement Learning with Experience Sharing. KDD workshop 2023 [PUB]
Uncertainty Quantification in Federated Learning for Heterogeneous Health Data KDD workshop 2023 [PUB]
A Systematic Evaluation of Federated Learning on Biomedical Natural Language Processing. KDD workshop 2023 [PUB]
Taming Heterogeneity to Deal with Test-Time Shift in Federated Learning. KDD workshop 2023 [PUB]
Federated Blood Supply Chain Demand Forecasting: A Case Study. KDD workshop 2023 [PUB]
Stochastic Clustered Federated Learning. KDD workshop 2023 [PUB]
A Privacy-Preserving Hybrid Federated Learning Framework for Financial Crime Detection. KDD workshop 2023 [PUB]
Exploring the Efficacy of Data-Decoupled Federated Learning for Image Classification and Medical Imaging Analysis. KDD workshop 2023 [PUB]
FedNoisy: A Federated Noisy Label Learning Benchmark KDD workshop 2023 [PUB]
Asynchronous Decentralized Federated Lifelong Learning for Landmark Localization in Medical Imaging KDD workshop 2023 [PUB]
Federated learning for competing risk analysis in healthcare. KDD workshop 2023 [PUB]
Federated Threat Detection for Smart Home IoT rules. KDD workshop 2023 [PUB]
Federated Unlearning for On-Device Recommendation UQ WSDM 2023 [PUB] [PDF]
Collaboration Equilibrium in Federated Learning THU KDD 2022 [PUB] [PDF] [CODE]
Connected Low-Loss Subspace Learning for a Personalization in Federated Learning Ulsan National Institute of Science and Technology KDD 2022 [PUB] [PDF] [CODE]
FedMSplit: Correlation-Adaptive Federated Multi-Task Learning across Multimodal Split Networks University of Virginia KDD 2022 [PUB]
Communication-Efficient Robust Federated Learning with Noisy Labels University of Pittsburgh KDD 2022 [PUB] [PDF]
FLDetector: Detecting Malicious Clients in Federated Learning via Checking Model-Updates Consistency USTC KDD 2022 [PUB] [PDF] [CODE]
Practical Lossless Federated Singular Vector Decomposition Over Billion-Scale Data HKUST KDD 2022 [PUB] [PDF] [CODE]
FedWalk: Communication Efficient Federated Unsupervised Node Embedding with Differential Privacy SJTU KDD 2022 [PUB] [PDF]
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Platform for Federated Graph Learning 🔥 Alibaba KDD (Best Paper Award) 2022 [PUB] [PDF] [CODE]
Fed-LTD: Towards Cross-Platform Ride Hailing via Federated Learning to Dispatch BUAA KDD 2022 [PUB] [PDF] [解读]
Felicitas: Federated Learning in Distributed Cross Device Collaborative Frameworks USTC KDD 2022 [PUB] [PDF]
No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices Renmin University of China KDD 2022 [PUB] [PDF]
FedAttack: Effective and Covert Poisoning Attack on Federated Recommendation via Hard Sampling THU KDD 2022 [PUB] [PDF] [CODE]
PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion The University of Queensland WSDM 2022 [PUB] [PDF]
Fed2: Feature-Aligned Federated Learning George Mason University; Microsoft; University of Maryland KDD 2021 [PUB] [PDF]
FedRS: Federated Learning with Restricted Softmax for Label Distribution Non-IID Data Nanjing University KDD 2021 [PUB] [CODE]
Federated Adversarial Debiasing for Fair and Trasnferable Representations Michigan State University KDD 2021 [PUB] [PAGE] [CODE] [SLIDE]
Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling USC KDD 2021 [PUB] [CODE] [解读]
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization Xidian University;JD Tech KDD 2021 [PUB] [PDF]
FLOP: Federated Learning on Medical Datasets using Partial Networks Duke University KDD 2021 [PUB] [PDF] [CODE]
A Practical Federated Learning Framework for Small Number of Stakeholders ETH Zürich WSDM 2021 [PUB] [CODE]
Federated Deep Knowledge Tracing USTC WSDM 2021 [PUB] [CODE]
FedFast: Going Beyond Average for Faster Training of Federated Recommender Systems University College Dublin KDD 2020 [PUB] [VIDEO]
Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data JD Tech KDD 2020 [PUB] [PDF] [VIDEO]
Federated Online Learning to Rank with Evolution Strategies Facebook AI Research WSDM 2019 [PUB] [CODE]

fl in top secure conference and journal

Federated Learning papers accepted by top Secure conference and journal, Including S&P(IEEE Symposium on Security and Privacy), CCS(Conference on Computer and Communications Security), USENIX Security(Usenix Security Symposium) and NDSS(Network and Distributed System Security Symposium).

fl in top secure conference and journal
Title Affiliation Venue Year Materials
FP-Fed: Privacy-Preserving Federated Detection of Browser Fingerprinting NDSS 2024 [PUB]
FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning NDSS 2024 [PUB]
Automatic Adversarial Adaption for Stealthy Poisoning Attacks in Federated Learning NDSS 2024 [PUB]
CrowdGuard: Federated Backdoor Detection in Federated Learning NDSS 2024 [PUB]
Protecting Label Distribution in Cross-Silo Federated Learning S&P 2024 [PUB]
FLShield: A Validation Based Federated Learning Framework to Defend Against Poisoning Attacks S&P 2024 [PUB]
BadVFL: Backdoor Attacks in Vertical Federated Learning S&P 2024 [PUB]
SHERPA: Explainable Robust Algorithms for Privacy-Preserved Federated Learning in Future Networks to Defend Against Data Poisoning Attacks S&P 2024 [PUB]
Loki: Large-scale Data Reconstruction Attack against Federated Learning through Model Manipulation S&P 2024 [PUB]
Poster: Towards Privacy-Preserving Federated Recommendation via Synthetic Interactions. S&P Workshop 2024 [PUB]
A Performance Analysis for Confidential Federated Learning. S&P Workshop 2024 [PUB]
Turning Privacy-preserving Mechanisms against Federated Learning University of Pavia CCS 2023 [PUB] [PDF]
MESAS: Poisoning Defense for Federated Learning Resilient against Adaptive Attackers University of Würzburg CCS 2023 [PUB]
martFL: Enabling Utility-Driven Data Marketplace with a Robust and Verifiable Federated Learning Architecture THU CCS 2023 [PUB] [PDF] [CODE]
Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks UIUC CCS 2023 [PUB] [PDF]
Poster: Verifiable Data Valuation with Strong Fairness in Horizontal Federated Learning NSYSU CCS 2023 [PUB]
Poster: Bridging Trust Gaps: Data Usage Transparency in Federated Data Ecosystems RWTH Aachen University CCS 2023 [PUB]
Every Vote Counts: Ranking-Based Training of Federated Learning to Resist Poisoning Attacks University of Massachusetts Amherst USENIX Security 2023 [PUB] [PDF]
PrivateFL: Accurate, Differentially Private Federated Learning via Personalized Data Transformation JHU USENIX Security 2023 [PUB] [CODE]
Gradient Obfuscation Gives a False Sense of Security in Federated Learning NCSU USENIX Security 2023 [PUB] [PDF] [CODE]
FedVal: Different good or different bad in federated learning AI Sweden USENIX Security 2023 [PUB] [PDF] [CODE]
Securing Federated Sensitive Topic Classification against Poisoning Attacks IMDEA Networks Institute NDSS 2023 [PUB] [PDF] [CODE]
PPA: Preference Profiling Attack Against Federated Learning NJUST NDSS 2023 [PUB] [PDF]
Turning Privacy-preserving Mechanisms against Federated Learning University of Pavia; TU Delft; University of Padua; Radboud University CCS 2023 [PUB] [PDF] [CODE]
CERBERUS: Exploring Federated Prediction of Security Events UCL London CCS 2022 [PUB] [PDF]
EIFFeL: Ensuring Integrity for Federated Learning UW-Madison CCS 2022 [PUB] [PDF]
Eluding Secure Aggregation in Federated Learning via Model Inconsistency SPRING Lab; EPFL CCS 2022 [PUB] [PDF] [CODE]
Federated Boosted Decision Trees with Differential Privacy University of Warwick CCS 2022 [PUB] [PDF] [CODE]
FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information Duke University S&P 2023 [PUB] [PDF]
Scalable and Privacy-Preserving Federated Principal Component Analysis EPFL; Tune Insight SA S&P 2023 [PUB] [PDF]
SafeFL: MPC-friendly Framework for Private and Robust Federated Learning TU Darmstadt S&P Workshop 2023 [PUB]
On the Pitfalls of Security Evaluation of Robust Federated Learning. umass S&P Workshop 2023 [PUB]
BayBFed: Bayesian Backdoor Defense for Federated Learning TU Darmstadt; UTSA S&P 2023 [PUB] [PDF]
3DFed: Adaptive and Extensible Framework for Covert Backdoor Attack in Federated Learning PolyU S&P 2023 [PUB] [CODE]
RoFL: Robustness of Secure Federated Learning. ETH Zurich S&P 2023 [PUB] [PDF] [CODE]
Flamingo: Multi-Round Single-Server Secure Aggregation with Applications to Private Federated Learning. upenn S&P 2023 [PUB] [CODE]
ELSA: Secure Aggregation for Federated Learning with Malicious Actors. S&P 2023
Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy Fudan University S&P 2023 [PUB] [PDF]
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning University of Massachusetts S&P 2022 [PUB] [VIDEO]
SIMC: ML Inference Secure Against Malicious Clients at Semi-Honest Cost Microsoft Research USENIX Security 2022 [PUB] [PDF] [CODE] [VIDEO] [SUPP]
Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors University of Vermont USENIX Security 2022 [PUB] [SLIDE] [VIDEO]
Label Inference Attacks Against Vertical Federated Learning ZJU USENIX Security 2022 [PUB] [SLIDE] [CODE] [VIDEO]
FLAME: Taming Backdoors in Federated Learning Technical University of Darmstadt USENIX Security 2022 [PUB] [SLIDE] [PDF] [VIDEO]
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning University at Buffalo, SUNY NDSS 2022 [PUB] [PDF] [VIDEO] [UC.]
Interpretable Federated Transformer Log Learning for Cloud Threat Forensics University of the Incarnate Word NDSS 2022 [PUB] [VIDEO] [UC.]
FedCRI: Federated Mobile Cyber-Risk Intelligence Technical University of Darmstadt NDSS 2022 [PUB] [VIDEO]
DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection Technical University of Darmstadt NDSS 2022 [PUB] [PDF] [VIDEO]
Private Hierarchical Clustering in Federated Networks NUS CCS 2021 [PUB] [PDF]
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Duke University NDSS 2021 [PUB] [PDF] [CODE] [VIDEO] [SLIDE]
POSEIDON: Privacy-Preserving Federated Neural Network Learning EPFL NDSS 2021 [PUB] [VIDEO]
Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning University of Massachusetts Amherst NDSS 2021 [PUB] [CODE] [VIDEO]
SAFELearn: Secure Aggregation for private FEderated Learning TU Darmstadt S&P Workshop 2021 [PUB]
Local Model Poisoning Attacks to Byzantine-Robust Federated Learning The Ohio State University USENIX Security 2020 [PUB] [PDF] [CODE] [VIDEO] [SLIDE]
A Reliable and Accountable Privacy-Preserving Federated Learning Framework using the Blockchain University of Kansas CCS (Poster) 2019 [PUB]
IOTFLA : A Secured and Privacy-Preserving Smart Home Architecture Implementing Federated Learning Université du Québéc á Montréal S&P Workshop 2019 [PUB]
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning 🔥 University of Massachusetts Amherst S&P 2019 [PUB] [VIDEO] [SLIDE] [CODE]
Practical Secure Aggregation for Privacy Preserving Machine Learning Google CCS 2017 [PUB] [PDF] [解读] [UC.] [UC]

fl in top cv conference and journal

Federated Learning papers accepted by top CV(computer vision) conference and journal, Including CVPR(Computer Vision and Pattern Recognition), ICCV(IEEE International Conference on Computer Vision), ECCV(European Conference on Computer Vision), MM(ACM International Conference on Multimedia), IJCV(International Journal of Computer Vision).

fl in top cv conference and journal
Title Affiliation Venue Year Materials
DualFed: Enjoying both Generalization and Personalization in Federated Learning via Hierachical Representations MM 2024 [PUB]
One-shot-but-not-degraded Federated Learning MM 2024 [PUB]
Overcoming Spatial-Temporal Catastrophic Forgetting for Federated Class-Incremental Learning MM 2024 [PUB]
FedDEO: Description-Enhanced One-Shot Federated Learning with Diffusion Models MM 2024 [PUB]
Decoupling General and Personalized Knowledge in Federated Learning via Additive and Low-rank Decomposition MM 2024 [PUB]
CoAst: Validation-Free Contribution Assessment for Federated Learning based on Cross-Round Valuation MM 2024 [PUB]
Spatio-temporal Heterogeneous Federated Learning for Time Series Classification with Multi-view Orthogonal Training MM 2024 [PUB]
FedEvalFair: A Privacy-Preserving and Statistically Grounded Federated Fairness Evaluation Framework MM 2024 [PUB]
One-Shot Sequential Federated Learning for Non-IID Data by Enhancing Local Model Diversity MM 2024 [PUB]
FedSLS: Exploring Federated Aggregation in Saliency Latent Space MM 2024 [PUB]
Cluster-driven Personalized Federated Recommendation with Interest-aware Graph Convolution Network for Multimedia MM 2024 [PUB]
FedBCGD: Communication-Efficient Accelerated Block Coordinate Gradient Descent for Federated Learning MM 2024 [PUB]
Federated Morozov Regularization for Shortcut Learning in Privacy Preserving Learning with Watermarked Image Data MM 2024 [PUB]
Cross-Modal Meta Consensus for Heterogeneous Federated Learning MM 2024 [PUB]
Masked Random Noise for Communication-Efficient Federated Learning MM 2024 [PUB]
Heterogeneity-Aware Federated Deep Multi-View Clustering towards Diverse Feature Representations MM 2024 [PUB]
Adaptive Hierarchical Aggregation for Federated Object Detection MM 2024 [PUB]
FedCAFE: Federated Cross-Modal Hashing with Adaptive Feature Enhancement MM 2024 [PUB]
Federated Fuzzy C-means with Schatten-p Norm Minimization MM 2024 [PUB]
Towards Effective Federated Graph Anomaly Detection via Self-boosted Knowledge Distillation MM 2024 [PUB]
Physics-Driven Spectrum-Consistent Federated Learning for Palmprint Verification IJCV 2024 [PUB]
Federated Learning with Local Openset Noisy Labels ECCV 2024 [PUB]
FedTSA: A Cluster-Based Two-Stage Aggregation Method for Model-Heterogeneous Federated Learning. ECCV 2024 [PUB]
Overcome Modal Bias in Multi-modal Federated Learning via Balanced Modality Selection ECCV 2024 [PUB]
BAFFLE: A Baseline of Backpropagation-Free Federated Learning ECCV 2024 [PUB]
PILoRA: Prototype Guided Incremental LoRA for Federated Class-Incremental Learning ECCV 2024 [PUB]
Fisher Calibration for Backdoor-Robust Heterogeneous Federated Learning ECCV 2024 [PUB]
Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents ECCV 2024 [PUB]
FedHARM: Harmonizing Model Architectural Diversity in Federated Learning ECCV 2024 [PUB]
SuperFedNAS: Cost-Efficient Federated Neural Architecture Search for On-device Inference. ECCV 2024 [PUB]
Personalized Federated Domain-Incremental Learning Based on Adaptive Knowledge Matching. ECCV 2024 [PUB]
Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning ECCV 2024 [PUB]
Towards Multi-modal Transformers in Federated Learning ECCV 2024 [PUB]
Local and Global Flatness for Federated Domain Generalization ECCV 2024 [PUB]
Feature Diversification and Adaptation for Federated Domain Generalization ECCV 2024 [PUB]
PFEDEDIT: Personalized Federated Learning via Automated Model Editing ECCV 2024 [PUB]
FedHCA2: Towards Hetero-Client Federated Multi-Task Learning SJTU CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Fair Federated Learning under Domain Skew with Local Consistency and Domain Diversity WHU CVPR 2024 [PUB] [PDF] [CODE]
Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts NWPU; HKUST CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
FedMef: Towards Memory-efficient Federated Dynamic Pruning CUHK CVPR 2024 [PUB] [SUPP] [PDF]
Communication-Efficient Federated Learning with Accelerated Client Gradient SNU CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Revamping Federated Learning Security from a Defender's Perspective: A Unified Defense with Homomorphic Encrypted Data Space IITH CVPR 2024 [PUB] [SUPP] [CODE]
Adaptive Hyper-graph Aggregation for Modality-Agnostic Federated Learning TJUT CVPR 2024 [PUB] [SUPP] [CODE]
Towards Efficient Replay in Federated Incremental Learning HUST CVPR 2024 [PUB] [SUPP] [PDF]
Mixed-Precision Quantization for Federated Learning on Resource-Constrained Heterogeneous Devices UT CVPR 2024 [PUB] [SUPP] [PDF]
Data Valuation and Detections in Federated Learning NUS CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Decentralized Directed Collaboration for Personalized Federated Learning NJUST CVPR 2024 [PUB] [SUPP] [PDF]
Unlocking the Potential of Prompt-Tuning in Bridging Generalized and Personalized Federated Learning UBC CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Global and Local Prompts Cooperation via Optimal Transport for Federated Learning ShanghaiTech University CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Rethinking the Representation in Federated Unsupervised Learning with Non-IID Data ZJU CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Relaxed Contrastive Learning for Federated Learning SNU CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Leak and Learn: An Attacker's Cookbook to Train Using Leaked Data from Federated Learning Purdue University CVPR 2024 [PUB] [SUPP] [PDF] [VIDEO]
Traceable Federated Continual Learning BUPT CVPR 2024 [PUB] [SUPP] [CODE]
Federated Online Adaptation for Deep Stereo University of Bologna CVPR 2024 [PUB] [SUPP] [PDF] [CODE] [PAGE] [VIDEO]
Federated Generalized Category Discovery UniTn CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Efficiently Assemble Normalization Layers and Regularization for Federated Domain Generalization ND CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Text-Enhanced Data-free Approach for Federated Class-Incremental Learning Monash University CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
PerAda: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees UIUC; NVIDIA CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning KAIST CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
FedUV: Uniformity and Variance for Heterogeneous Federated Learning UC Davis CVPR 2024 [PUB] [SUPP] [PDF]
FedAS: Bridging Inconsistency in Personalized Federated Learning WHU CVPR 2024 [PUB] [CODE]
FedSelect: Personalized Federated Learning with Customized Selection of Parameters for Fine-Tuning Lapis Labs CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Device-Wise Federated Network Pruning PITT CVPR 2024 [PUB] [SUPP]
Byzantine-robust Decentralized Federated Learning via Dual-domain Clustering and Trust Bootstrapping HNU; PolyU; AIRS CVPR 2024 [PUB] [SUPP]
DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning HKUST; PolyU CVPR 2024 [PUB] [SUPP] [PDF]
An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning SJTU CVPR 2024 [PUB] [SUPP] [PDF] [CODE] [POSTER] [SLIDES]
An Aggregation-Free Federated Learning for Tackling Data Heterogeneity A* STAR CVPR 2024 [PUB] [SUPP] [PDF]
FLHetBench: Benchmarking Device and State Heterogeneity in Federated Learning BUAA; HKU CVPR 2024 [PUB] [SUPP] [CODE] [PAGE] [POSTER] [VIDEO]
Collaborative Visual Place Recognition through Federated Learning CVPR workshop 2024 [PUB] [SUPP] [PDF]
FedProK: Trustworthy Federated Class-Incremental Learning via Prototypical Feature Knowledge Transfer CVPR workshop 2024 [PUB] [SUPP] [PDF]
Federated Hyperparameter Optimization Through Reward-Based Strategies: Challenges and Insights CVPR workshop 2024 [PUB]
On the Efficiency of Privacy Attacks in Federated Learning CVPR workshop 2024 [PUB] [PDF]
FedCE: Personalized Federated Learning Method based on Clustering Ensembles BJTU MM 2023 [PUB]
FedVQA: Personalized Federated Visual Question Answering over Heterogeneous Scenes Leiden University MM 2023 [PUB]
Towards Fast and Stable Federated Learning: Confronting Heterogeneity via Knowledge Anchor XJTU MM 2023 [PUB] [PDF] [CODE]
Federated Deep Multi-View Clustering with Global Self-Supervision UESTC MM 2023 [PUB] [PDF]
FedAA: Using Non-sensitive Modalities to Improve Federated Learning while Preserving Image Privacy ZJU MM 2023 [PUB]
Prototype-guided Knowledge Transfer for Federated Unsupervised Cross-modal Hashing SDNU MM 2023 [PUB] [CODE]
Joint Local Relational Augmentation and Global Nash Equilibrium for Federated Learning with Non-IID Data ZJU MM 2023 [PUB] [PDF]
FedCD: A Classifier Debiased Federated Learning Framework for Non-IID Data BUPT MM 2023 [PUB]
Federated Learning with Label-Masking Distillation UCAS MM 2023 [PUB] [CODE]
Cross-Silo Prototypical Calibration for Federated Learning with Non-IID Data SDU MM 2023 [PUB] [PDF] [CODE]
A Four-Pronged Defense Against Byzantine Attacks in Federated Learning HUST MM 2023 [PUB] [PDF]
Client-Adaptive Cross-Model Reconstruction Network for Modality-Incomplete Multimodal Federated Learning CAS; Peng Cheng Laboratory; UCAS MM 2023 [PUB]
FedGH: Heterogeneous Federated Learning with Generalized Global Header NKU MM 2023 [PUB] [PDF] [CODE]
Cuing Without Sharing: A Federated Cued Speech Recognition Framework via Mutual Knowledge Distillation CUHK MM 2023 [PUB] [PDF] [CODE]
AffectFAL: Federated Active Affective Computing with Non-IID Data TJUT MM 2023 [PUB] [CODE]
Improving Federated Person Re-Identification through Feature-Aware Proximity and Aggregation SZU MM 2023 [PUB]
Towards Attack-tolerant Federated Learning via Critical Parameter Analysis KAIST ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
Efficient Model Personalization in Federated Learning via Client-Specific Prompt Generation NTU; NVIDIA ICCV 2023 [PUB] [PDF] [SUPP]
Generative Gradient Inversion via Over-Parameterized Networks in Federated Learning A*STAR ICCV 2023 [PUB] [CODE] [SUPP]
GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning SJTU ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
Workie-Talkie: Accelerating Federated Learning by Overlapping Computing and Communications via Contrastive Regularization University of Houston ICCV 2023 [PUB] [SUPP]
PGFed: Personalize Each Client's Global Objective for Federated Learning University of Pittsburgh ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning UCF ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning TCL AI Lab ICCV 2023 [PUB] [PDF] [SUPP]
FedPD: Federated Open Set Recognition with Parameter Disentanglement City University of Hong Kong ICCV 2023 [PUB] [CODE]
TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation ETH Zurich; Sony AI ICCV 2023 [PUB] [PDF] [CODE]
Towards Instance-adaptive Inference for Federated Learning A*STAR ICCV 2023 [PUB] [PDF] [CODE]
Communication-efficient Federated Learning with Single-Step Synthetic Features Compressor for Faster Convergence SCU; Engineering Research Center of Machine Learning and Industry Intelligence ICCV 2023 [PUB] [PDF] [CODE]
zPROBE: Zero Peek Robustness Checks for Federated Learning Purdue University ICCV 2023 [PUB] [PDF] [SUPP]
ProtoFL: Unsupervised Federated Learning via Prototypical Distillation KakaoBank Corp. ICCV 2023 [PUB] [PDF]
MAS: Towards Resource-Efficient Federated Multiple-Task Learning Sony AI ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
FSAR: Federated Skeleton-based Action Recognition with Adaptive Topology Structure and Knowledge Distillation PKU ICCV 2023 [PUB] [PDF] [SUPP]
When Do Curricula Work in Federated Learning? UCSD ICCV 2023 [PUB] [PDF] [SUPP]
Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples Duke University ICCV 2023 [PUB] [PDF] [CODE]
Multi-Metrics Adaptively Identifies Backdoors in Federated Learning SCUT ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier ZJU ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation Ludwig Maximilian University of Munich; Siemens Technology ICCV 2023 [PUB] [PDF] [SUPP]
Bold but Cautious: Unlocking the Potential of Personalized Federated Learning through Cautiously Aggressive Collaboration BUAA ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
Global Balanced Experts for Federated Long-Tailed Learning CUHK-Shenzhen ICCV 2023 [PUB] [CODE] [SUPP]
Knowledge-Aware Federated Active Learning with Non-IID Data The University of Sydney ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
Enhancing Privacy Preservation in Federated Learning via Learning Rate Perturbation BUPT ICCV 2023 [PUB] [SUPP]
Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels CMU ICCV 2023 [PUB] [PDF] [SUPP]
Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat Rice University ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
Robust Heterogeneous Federated Learning under Data Corruption WHU ICCV 2023 [PUB] [CODE] [SUPP]
Personalized Semantics Excitation for Federated Image Classification Tulane University ICCV 2023 [PUB] [CODE]
Reducing Training Time in Cross-Silo Federated Learning Using Multigraph Topology AIOZ ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
Window-based Model Averaging Improves Generalization in Heterogeneous Federated Learning. Politecnico di Torino ICCV workshop 2023 [PUB] [PDF]
Experience Replay as an Effective Strategy for Optimizing Decentralized Federated Learning. University of Catania ICCV workshop 2023 [PUB]
FedRCIL: Federated Knowledge Distillation for Representation based Contrastive Incremental Learning. Centre for Research and Technology Hellas; University of West Attica ICCV workshop 2023 [PUB] [CODE]
FedLID: Self-Supervised Federated Learning for Leveraging Limited Image Data. Centre for Research and Technology Hellas; University of West Attica ICCV workshop 2023 [PUB]
Rethinking Federated Learning With Domain Shift: A Prototype View WHU CVPR 2023 [PUB] [CODE]
Class Balanced Adaptive Pseudo Labeling for Federated Semi-Supervised Learning ECNU CVPR 2023 [PUB] [CODE]
DaFKD: Domain-Aware Federated Knowledge Distillation HUST CVPR 2023 [PUB] [CODE]
The Resource Problem of Using Linear Layer Leakage Attack in Federated Learning Purdue University CVPR 2023 [PUB] [PDF]
FedSeg: Class-Heterogeneous Federated Learning for Semantic Segmentation ZJU CVPR 2023 [PUB]
On the Effectiveness of Partial Variance Reduction in Federated Learning With Heterogeneous Data DTU CVPR 2023 [PUB] [PDF]
Elastic Aggregation for Federated Optimization Meituan CVPR 2023 [PUB]
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning UCLA CVPR 2023 [PUB] [PDF]
Adaptive Channel Sparsity for Federated Learning Under System Heterogeneity UM CVPR 2023 [PUB]
ScaleFL: Resource-Adaptive Federated Learning With Heterogeneous Clients GaTech CVPR 2023 [PUB] [CODE]
Reliable and Interpretable Personalized Federated Learning TJU CVPR 2023 [PUB]
Federated Domain Generalization With Generalization Adjustment SJTU CVPR 2023 [PUB] [CODE]
Make Landscape Flatter in Differentially Private Federated Learning THU CVPR 2023 [PUB] [PDF] [CODE]
Confidence-Aware Personalized Federated Learning via Variational Expectation Maximization KU Leuven CVPR 2023 [PUB] [PDF] [CODE]
STDLens: Model Hijacking-Resilient Federated Learning for Object Detection GaTech CVPR 2023 [PUB] [PDF] [CODE]
Re-Thinking Federated Active Learning Based on Inter-Class Diversity KAIST CVPR 2023 [PUB] [PDF] [CODE]
Learning Federated Visual Prompt in Null Space for MRI Reconstruction A*STAR CVPR 2023 [PUB] [PDF] [CODE]
Fair Federated Medical Image Segmentation via Client Contribution Estimation CUHK CVPR 2023 [PUB] [PDF] [CODE]
Federated Learning With Data-Agnostic Distribution Fusion NJU CVPR 2023 [PUB] [CODE]
How To Prevent the Poor Performance Clients for Personalized Federated Learning? CSU CVPR 2023 [PUB]
GradMA: A Gradient-Memory-Based Accelerated Federated Learning With Alleviated Catastrophic Forgetting ECNU CVPR 2023 [PUB] [PDF] [CODE]
Bias-Eliminating Augmentation Learning for Debiased Federated Learning NTU CVPR 2023 [PUB]
Federated Incremental Semantic Segmentation CAS; UCAS CVPR 2023 [PUB] [PDF] [CODE]
Asynchronous Federated Continual Learning University of Padova CVPR workshop 2023 [PUB] [PDF] [SILDES] [CODE]
Mixed Quantization Enabled Federated Learning To Tackle Gradient Inversion Attacks UMBC CVPR workshop 2023 [PUB] [CODE]
OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework Meituan CVPR workshop 2023 [PUB] [PDF] [CODE]
Federated Learning in Non-IID Settings Aided by Differentially Private Synthetic Data utexas CVPR workshop 2023 [PUB] [SUPP] [PDF] [CODE]
TimelyFL: Heterogeneity-Aware Asynchronous Federated Learning With Adaptive Partial Training USC CVPR workshop 2023 [PUB] [PDF]
Many-Task Federated Learning: A New Problem Setting and a Simple Baseline utexas CVPR workshop 2023 [PUB] [CODE]
Confederated Learning: Going Beyond Centralization CAS; UCAS MM 2022 [PUB]
Few-Shot Model Agnostic Federated Learning WHU MM 2022 [PUB] [CODE]
Feeling Without Sharing: A Federated Video Emotion Recognition Framework Via Privacy-Agnostic Hybrid Aggregation TJUT MM 2022 [PUB]
FedLTN: Federated Learning for Sparse and Personalized Lottery Ticket Networks ECCV 2022 [PUB] [SUPP]
Auto-FedRL: Federated Hyperparameter Optimization for Multi-Institutional Medical Image Segmentation ECCV 2022 [PUB] [SUPP] [PDF] [CODE]
Improving Generalization in Federated Learning by Seeking Flat Minima Politecnico di Torino ECCV 2022 [PUB] [SUPP] [PDF] [CODE]
AdaBest: Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation ECCV 2022 [PUB] [SUPP] [PDF] [CODE] [PAGE]
SphereFed: Hyperspherical Federated Learning ECCV 2022 [PUB] [SUPP] [PDF]
Federated Self-Supervised Learning for Video Understanding ECCV 2022 [PUB] [PDF] [CODE]
FedVLN: Privacy-Preserving Federated Vision-and-Language Navigation ECCV 2022 [PUB] [SUPP] [PDF] [CODE]
Addressing Heterogeneity in Federated Learning via Distributional Transformation ECCV 2022 [PUB] [CODE]
FedX: Unsupervised Federated Learning with Cross Knowledge Distillation KAIST ECCV 2022 [PUB] [SUPP] [PDF] [CODE]
Personalizing Federated Medical Image Segmentation via Local Calibration Xiamen University ECCV 2022 [PUB] [SUPP] [PDF] [CODE]
ATPFL: Automatic Trajectory Prediction Model Design Under Federated Learning Framework HIT CVPR 2022 [PUB]
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning Stanford CVPR 2022 [PUB] [SUPP] [PDF] [CODE] [VIDEO]
FedCorr: Multi-Stage Federated Learning for Label Noise Correction Singapore University of Technology and Design CVPR 2022 [PUB] [SUPP] [PDF] [CODE] [VIDEO]
FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning Duke University CVPR 2022 [PUB] [SUPP] [PDF]
Layer-Wised Model Aggregation for Personalized Federated Learning PolyU CVPR 2022 [PUB] [SUPP] [PDF]
Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning University of Central Florida CVPR 2022 [PUB] [SUPP] [PDF] [CODE]
Federated Learning With Position-Aware Neurons Nanjing University CVPR 2022 [PUB] [SUPP] [PDF]
RSCFed: Random Sampling Consensus Federated Semi-Supervised Learning HKUST CVPR 2022 [PUB] [SUPP] [PDF] [CODE]
Learn From Others and Be Yourself in Heterogeneous Federated Learning Wuhan University CVPR 2022 [PUB] [CODE] [VIDEO]
Robust Federated Learning With Noisy and Heterogeneous Clients Wuhan University CVPR 2022 [PUB] [SUPP] [CODE]
ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning Arizona State University CVPR 2022 [PUB] [SUPP] [PDF] [CODE]
FedDC: Federated Learning With Non-IID Data via Local Drift Decoupling and Correction National University of Defense Technology CVPR 2022 [PUB] [PDF] [CODE] [解读]
Federated Class-Incremental Learning CAS; Northwestern University; UTS CVPR 2022 [PUB] [PDF] [CODE]
Fine-Tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning PKU; JD Explore Academy; The University of Sydney CVPR 2022 [PUB] [PDF]
Differentially Private Federated Learning With Local Regularization and Sparsification CAS CVPR 2022 [PUB] [PDF]
Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage University of Tennessee; Oak Ridge National Laboratory; Google Research CVPR 2022 [PUB] [PDF] [CODE] [VIDEO]
CD2-pFed: Cyclic Distillation-Guided Channel Decoupling for Model Personalization in Federated Learning SJTU CVPR 2022 [PUB] [PDF]
Closing the Generalization Gap of Cross-Silo Federated Medical Image Segmentation Univ. of Pittsburgh; NVIDIA CVPR 2022 [PUB] [PDF]
Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning HHI CVPR workshop 2022 [PUB] [PDF] [SILDES] [VIDEO]
MPAF: Model Poisoning Attacks to Federated Learning Based on Fake Clients Duke University CVPR workshop 2022 [PUB] [PDF] [SILDES] [VIDEO]
Communication-Efficient Federated Data Augmentation on Non-IID Data UESTC CVPR workshop 2022 [PUB]
Does Federated Dropout Actually Work? Stanford CVPR workshop 2022 [PUB] [VIDEO]
FedIris: Towards More Accurate and Privacy-preserving Iris Recognition via Federated Template Communication USTC; CRIPAC; CASIA CVPR workshop 2022 [PUB] [SLIDES] [VIDEO]
Multi-Institutional Collaborations for Improving Deep Learning-Based Magnetic Resonance Image Reconstruction Using Federated Learning Johns Hopkins University CVPR 2021 [PUB] [PDF] [CODE]
Model-Contrastive Federated Learning 🔥 NUS; UC Berkeley CVPR 2021 [PUB] [PDF] [CODE] [解读]
FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space 🔥 CUHK CVPR 2021 [PUB] [PDF] [CODE]
Soteria: Provable Defense Against Privacy Leakage in Federated Learning From Representation Perspective Duke University CVPR 2021 [PUB] [PDF] [CODE]
Federated Learning for Non-IID Data via Unified Feature Learning and Optimization Objective Alignment PKU ICCV 2021 [PUB]
Ensemble Attention Distillation for Privacy-Preserving Federated Learning University at Buffalo ICCV 2021 [PUB] [PDF]
Collaborative Unsupervised Visual Representation Learning from Decentralized Data NTU; SenseTime ICCV 2021 [PUB] [PDF]
Joint Optimization in Edge-Cloud Continuum for Federated Unsupervised Person Re-identification NTU MM 2021 [PUB] [PDF]
Federated Visual Classification with Real-World Data Distribution MIT; Google ECCV 2020 [PUB] [PDF] [VIDEO]
InvisibleFL: Federated Learning over Non-Informative Intermediate Updates against Multimedia Privacy Leakages MM 2020 [PUB]
Performance Optimization of Federated Person Re-identification via Benchmark Analysis data. NTU MM 2020 [PUB] [PDF] [CODE] [解读]

fl in top nlp conference and journal

Federated Learning papers accepted by top AI and NLP conference and journal, including ACL(Annual Meeting of the Association for Computational Linguistics), NAACL(North American Chapter of the Association for Computational Linguistics), EMNLP(Conference on Empirical Methods in Natural Language Processing) and COLING(International Conference on Computational Linguistics).

fl in top nlp conference and journal
Title Affiliation Venue Year Materials
A Hassle-free Algorithm for Strong Differential Privacy in Federated Learning Systems EMNLP 2024 [PUB]
Safely Learning with Private Data: A Federated Learning Framework for Large Language Model EMNLP 2024 [PUB]
FEDKIM: Adaptive Federated Knowledge Injection into Medical Foundation Models EMNLP 2024 [PUB]
Fisher Information-based Efficient Curriculum Federated Learning with Large Language Models EMNLP 2024 [PUB]
Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models EMNLP 2024 [PUB]
Promoting Data and Model Privacy in Federated Learning through Quantized LoRA EMNLP Findings 2024 [PUB]
Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models EMNLP Findings 2024 [PUB]
Generalizable Multilingual Hate Speech Detection on Low Resource Indian Languages using Fair Selection in Federated Learning NAACL 2024 [PUB]
Open-Vocabulary Federated Learning with Multimodal Prototyping NAACL 2024 [PUB]
Navigation as Attackers Wish? Towards Building Robust Embodied Agents under Federated Learning NAACL 2024 [PUB]
FedLFC: Towards Efficient Federated Multilingual Modeling with LoRA-based Language Family Clustering. NAACL Findings 2024 [PUB]
Personalized Federated Learning for Text Classification with Gradient-Free Prompt Tuning. NAACL Findings 2024 [PUB]
Can Public Large Language Models Help Private Cross-device Federated Learning? NAACL Findings 2024 [PUB]
Fair Federated Learning with Biased Vision-Language Models ACL Findings 2024 [PUB]
Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization Auburn University EMNLP 2023 [PUB] [PDF] [CODE]
Federated Meta-Learning for Emotion and Sentiment Aware Multi-modal Complaint Identification IIT Patna EMNLP 2023 [PUB] [CODE]
FedID: Federated Interactive Distillation for Large-Scale Pretraining Language Models YNU EMNLP 2023 [PUB] [CODE]
FedTherapist: Mental Health Monitoring with User-Generated Linguistic Expressions on Smartphones via Federated Learning KAIST EMNLP 2023 [PUB] [PDF]
Coordinated Replay Sample Selection for Continual Federated Learning CMU EMNLP industry Track 2023 [PUB] [PDF]
Tunable Soft Prompts are Messengers in Federated Learning SYSU EMNLP Findings 2023 [PUB] [PDF] [CODE]
Federated Learning for Semantic Parsing: Task Formulation, Evaluation Setup, New Algorithms OSU ACL 2023 [PUB] [PDF] [CODE]
FEDLEGAL: The First Real-World Federated Learning Benchmark for Legal NLP HIT; Peng Cheng Lab ACL 2023 [PUB] [CODE]
Client-Customized Adaptation for Parameter-Efficient Federated Learning ACL Findings 2023 [PUB]
Communication Efficient Federated Learning for Multilingual Neural Machine Translation with Adapter ACL Findings 2023 [PUB] [PDF] [CODE]
Federated Domain Adaptation for Named Entity Recognition via Distilling with Heterogeneous Tag Sets ACL Findings 2023 [PUB]
FedPETuning: When Federated Learning Meets the Parameter-Efficient Tuning Methods of Pre-trained Language Models ACL Findings 2023 [PUB]
Federated Learning of Gboard Language Models with Differential Privacy ACL Industry Track 2023 [PUB] [PDF]
Backdoor Attacks in Federated Learning by Rare Embeddings and Gradient Ensembling SNU EMNLP 2022 [PUB] [PDF]
A Federated Approach to Predicting Emojis in Hindi Tweets University of Alberta EMNLP 2022 [PUB] [PDF] [CODE]
Federated Model Decomposition with Private Vocabulary for Text Classification HIT; Peng Cheng Lab EMNLP 2022 [PUB] [CODE]
Fair NLP Models with Differentially Private Text Encoders Univ. Lille EMNLP 2022 [PUB] [PDF] [CODE]
Federated Continual Learning for Text Classification via Selective Inter-client Transfer DRIMCo GmbH; LMU EMNLP Findings 2022 [PUB] [PDF] [CODE]
Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation kg. Lehigh University EMNLP Findings 2022 [PUB] [PDF] [CODE]
Dim-Krum: Backdoor-Resistant Federated Learning for NLP with Dimension-wise Krum-Based Aggregation PKU EMNLP Findings 2022 [PUB] [PDF]
Scaling Language Model Size in Cross-Device Federated Learning Google ACL workshop 2022 [PUB] [PDF]
Intrinsic Gradient Compression for Scalable and Efficient Federated Learning Oxford ACL workshop 2022 [PUB] [PDF]
ActPerFL: Active Personalized Federated Learning Amazon ACL workshop 2022 [PUB] [PAGE]
FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks 🔥 USC NAACL 2022 [PUB] [PDF] [CODE]
Federated Learning with Noisy User Feedback USC; Amazon NAACL 2022 [PUB] [PDF]
Training Mixed-Domain Translation Models via Federated Learning Amazon NAACL 2022 [PUB] [PAGE] [PDF]
Pretrained Models for Multilingual Federated Learning Johns Hopkins University NAACL 2022 [PUB] [PDF] [CODE]
Federated Chinese Word Segmentation with Global Character Associations University of Washington ACL workshop 2021 [PUB] [CODE]
Efficient-FedRec: Efficient Federated Learning Framework for Privacy-Preserving News Recommendation USTC EMNLP 2021 [PUB] [PDF] [CODE] [VIDEO]
Improving Federated Learning for Aspect-based Sentiment Analysis via Topic Memories CUHK (Shenzhen) EMNLP 2021 [PUB] [CODE] [VIDEO]
A Secure and Efficient Federated Learning Framework for NLP University of Connecticut EMNLP 2021 [PUB] [PDF] [VIDEO]
Distantly Supervised Relation Extraction in Federated Settings UCAS EMNLP workshop 2021 [PUB] [PDF] [CODE]
Federated Learning with Noisy User Feedback USC; Amazon NAACL workshop 2021 [PUB] [PDF]
An Investigation towards Differentially Private Sequence Tagging in a Federated Framework Universität Hamburg NAACL workshop 2021 [PUB]
Understanding Unintended Memorization in Language Models Under Federated Learning Google NAACL workshop 2021 [PUB] [PDF]
FedED: Federated Learning via Ensemble Distillation for Medical Relation Extraction CAS EMNLP 2020 [PUB] [VIDEO] [解读]
Empirical Studies of Institutional Federated Learning For Natural Language Processing Ping An Technology EMNLP workshop 2020 [PUB]
Federated Learning for Spoken Language Understanding PKU COLING 2020 [PUB]
Two-stage Federated Phenotyping and Patient Representation Learning Boston Children’s Hospital Harvard Medical School ACL workshop 2019 [PUB] [PDF] [CODE] [UC.]

fl in top ir conference and journal

Federated Learning papers accepted by top Information Retrieval conference and journal, including SIGIR(Annual International ACM SIGIR Conference on Research and Development in Information Retrieval).

fl in top ir conference and journal
Title Affiliation Venue Year Materials
ReFer: Retrieval-Enhanced Vertical Federated Recommendation for Full Set User Benefit THU SIGIR 2024 [PUB]
Revisit Targeted Model Poisoning on Federated Recommendation: Optimize via Multi-objective Transport ZJU SIGIR 2024 [PUB]
FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation UQ SIGIR 2024 [PUB] [PDF] [CODE]
FedUD: Exploiting Unaligned Data for Cross-Platform Federated Click-Through Rate Prediction Alibaba Group SIGIR 2024 [PUB]
Personalized Federated Relation Classification over Heterogeneous Texts NUDT SIGIR 2023 [PUB]
Fine-Grained Preference-Aware Personalized Federated POI Recommendation with Data Sparsity SDU SIGIR 2023 [PUB]
Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures UQ SIGIR 2023 [PUB] [PDF]
FedAds: A Benchmark for Privacy-Preserving CVR Estimation with Vertical Federated Learning Alibaba Group SIGIR 2023 [PUB] [PDF] [CODE]
Edge-cloud Collaborative Learning with Federated and Centralized Features (short-paper) ZJU SIGIR 2023 [PUB] [PDF]
FLIRT: Federated Learning for Information Retrieval (extended-abstract) IMT Lucca SIGIR 2023 [PUB]
Is Non-IID Data a Threat in Federated Online Learning to Rank? The University of Queensland SIGIR 2022 [PUB] [CODE]
FedCT: Federated Collaborative Transfer for Recommendation Rutgers University SIGIR 2021 [PUB] [PDF] [CODE]
On the Privacy of Federated Pipelines Technical University of Munich SIGIR 2021 [PUB]
FedCMR: Federated Cross-Modal Retrieval. Dalian University of Technology SIGIR 2021 [PUB] [CODE]
Meta Matrix Factorization for Federated Rating Predictions. SDU SIGIR 2020 [PUB] [PDF]

fl in top db conference and journal

Federated Learning papers accepted by top Database conference and journal, including SIGMOD(ACM SIGMOD Conference) , ICDE(IEEE International Conference on Data Engineering) and VLDB(Very Large Data Bases Conference).

fl in top db conference and journal
Title Affiliation Venue Year Materials
FedMix: Boosting with Data Mixture for Vertical Federated Learning ICDE 2024 [PUB]
FedCross: Towards Accurate Federated Learning via Multi-Model Cross-Aggregation ICDE 2024 [PUB]
Clients Help Clients: Alternating Collaboration for Semi-Supervised Federated Learning ICDE 2024 [PUB]
Semi-Asynchronous Online Federated Crowdsourcing ICDE 2024 [PUB]
AdaFGL: A New Paradigm for Federated Node Classification with Topology Heterogeneity ICDE 2024 [PUB]
MergeSFL: Split Federated Learning with Feature Merging and Batch Size Regulation ICDE 2024 [PUB]
LightTR: A Lightweight Framework for Federated Trajectory Recovery ICDE 2024 [PUB]
Feed: Towards Personalization-Effective Federated Learning ICDE 2024 [PUB]
Label Noise Correction for Federated Learning: A Secure, Efficient and Reliable Realization ICDE 2024 [PUB]
Fast, Robust and Interpretable Participant Contribution Estimation for Federated Learning ICDE 2024 [PUB]
HeteFedRec: Federated Recommender Systems with Model Heterogeneity ICDE 2024 [PUB]
Hide Your Model: A Parameter Transmission-free Federated Recommender System ICDE 2024 [PUB]
FedCTQ: A Federated-Based Framework for Accurate and Efficient Contact Tracing Query ICDE 2024 [PUB]
Preventing the Popular Item Embedding Based Attack in Federated Recommendations ICDE 2024 [PUB]
RobFL: Robust Federated Learning via Feature Center Separation and Malicious Center Detection ICDE 2024 [PUB]
Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly TUM DEEM@SIGMOD 2024 [PUB]
FedSQ: A Secure System for Federated Vector Similarity Queries VLDB 2024 [PUB]
FedSM: A Practical Federated Shared Mobility System VLDB 2024 [PUB]
OFL-W3: A One-Shot Federated Learning System on Web 3.0 VLDB 2024 [PUB]
Contributions Estimation in Federated Learning: A Comprehensive Experimental Evaluation VLDB 2024 [PUB]
OFL-W3: A One-shot Federated Learning System on Web 3.0 VLDB 2024 [PUB]
Uldp-FL: Federated Learning with Across Silo User-Level Differential Privacy. VLDB 2024 [PUB]
FedSM: A Practical Federated Shared Mobility System. VLDB 2024 [PUB]
FedSQ: A Secure System for Federated Vector Similarity Queries VLDB 2024 [PUB]
Performance-Based Pricing of Federated Learning via Auction Alibaba Group VLDB 2024 [PUB] [CODE]
A Blockchain System for Clustered Federated Learning with Peer-to-Peer Knowledge Transfer NJU VLDB 2024 [PUB] [CODE]
Communication Efficient and Provable Federated Unlearning SDU; KAUST VLDB 2024 [PUB] [PDF] [CODE]
Enhancing Decentralized Federated Learning for Non-IID Data on Heterogeneous Devices USTC ICDE 2023 [PUB]
Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs Columbia University ICDE 2023 [PUB] [CODE]
FedKNOW: Federated Continual Learning with Signature Task Knowledge Integration at Edge BIT ICDE 2023 [PUB] [PDF]
Lumos: Heterogeneity-aware Federated Graph Learning over Decentralized Devices SJTU ICDE 2023 [PUB] [PDF]
Federated IoT Interaction Vulnerability Analysis MSU ICDE 2023 [PUB]
Distribution-Regularized Federated Learning on Non-IID Data BUAA ICDE 2023 [PUB]
Fed-SC: One-Shot Federated Subspace Clustering over High-Dimensional Data ShanghaiTech University ICDE 2023 [PUB] [CODE]
FLBooster: A Unified and Efficient Platform for Federated Learning Acceleration ZJU ICDE 2023 [PUB]
FedGTA: Topology-aware Averaging for Federated Graph Learning. BIT VLDB 2023 [PUB] [CODE]
FS-Real: A Real-World Cross-Device Federated Learning Platform. Alibaba Group VLDB 2023 [PUB] [PDF] [CODE]
Federated Calibration and Evaluation of Binary Classifiers. meta VLDB 2023 [PUB] [PDF] [CODE]
Olive: Oblivious Federated Learning on Trusted Execution Environment Against the Risk of Sparsification. Kyoto University VLDB 2023 [PUB] [PDF] [CODE]
Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System. NUS VLDB 2023 [PUB] [CODE]
Differentially Private Vertical Federated Clustering. Purdue University VLDB 2023 [PUB] [PDF] [CODE]
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity. 🔥 Alibaba VLDB 2023 [PUB] [PDF] [CODE]
Secure Shapley Value for Cross-Silo Federated Learning. Kyoto University VLDB 2023 [PUB] [PDF] [CODE]
OpBoost: A Vertical Federated Tree Boosting Framework Based on Order-Preserving Desensitization ZJU VLDB 2022 [PUB] [PDF] [CODE]
Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy. NUS VLDB 2022 [PUB] [CODE]
Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Update PKU VLDB 2022 [PUB] [PDF] [CODE]
FedTSC: A Secure Federated Learning System for Interpretable Time Series Classification. HIT VLDB 2022 [PUB] [CODE]
Improving Fairness for Data Valuation in Horizontal Federated Learning The UBC ICDE 2022 [PUB] [PDF]
FedADMM: A Robust Federated Deep Learning Framework with Adaptivity to System Heterogeneity USTC ICDE 2022 [PUB] [PDF] [CODE]
FedMP: Federated Learning through Adaptive Model Pruning in Heterogeneous Edge Computing. USTC ICDE 2022 [PUB]
Federated Learning on Non-IID Data Silos: An Experimental Study. 🔥 NUS ICDE 2022 [PUB] [PDF] [CODE]
Enhancing Federated Learning with Intelligent Model Migration in Heterogeneous Edge Computing USTC ICDE 2022 [PUB]
Samba: A System for Secure Federated Multi-Armed Bandits Univ. Clermont Auvergne ICDE 2022 [PUB] [CODE]
FedRecAttack: Model Poisoning Attack to Federated Recommendation ZJU ICDE 2022 [PUB] [PDF] [CODE]
Enhancing Federated Learning with In-Cloud Unlabeled Data USTC ICDE 2022 [PUB]
Efficient Participant Contribution Evaluation for Horizontal and Vertical Federated Learning USTC ICDE 2022 [PUB]
An Introduction to Federated Computation University of Warwick; Facebook SIGMOD Tutorial 2022 [PUB]
BlindFL: Vertical Federated Machine Learning without Peeking into Your Data PKU; Tencent SIGMOD 2022 [PUB] [PDF]
An Efficient Approach for Cross-Silo Federated Learning to Rank BUAA ICDE 2021 [PUB] [RELATED PAPER(ZH)]
Feature Inference Attack on Model Predictions in Vertical Federated Learning NUS ICDE 2021 [PUB] [PDF] [CODE]
Efficient Federated-Learning Model Debugging USTC ICDE 2021 [PUB]
Federated Matrix Factorization with Privacy Guarantee Purdue VLDB 2021 [PUB]
Projected Federated Averaging with Heterogeneous Differential Privacy. Renmin University of China VLDB 2021 [PUB] [CODE]
Enabling SQL-based Training Data Debugging for Federated Learning Simon Fraser University VLDB 2021 [PUB] [PDF] [CODE]
Refiner: A Reliable Incentive-Driven Federated Learning System Powered by Blockchain ZJU VLDB 2021 [PUB]
Tanium Reveal: A Federated Search Engine for Querying Unstructured File Data on Large Enterprise Networks Tanium Inc. VLDB 2021 [PUB] [VIDEO]
VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning PKU SIGMOD 2021 [PUB]
ExDRa: Exploratory Data Science on Federated Raw Data SIEMENS SIGMOD 2021 [PUB]
Joint blockchain and federated learning-based offloading in harsh edge computing environments TJU SIGMOD workshop 2021 [PUB]
Privacy Preserving Vertical Federated Learning for Tree-based Models NUS VLDB 2020 [PUB] [PDF] [VIDEO] [CODE]

fl in top network conference and journal

Federated Learning papers accepted by top Database conference and journal, including SIGCOMM(Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication), INFOCOM(IEEE Conference on Computer Communications), MobiCom(ACM/IEEE International Conference on Mobile Computing and Networking), NSDI(Symposium on Networked Systems Design and Implementation) and WWW(The Web Conference).

fl in top network conference and journal
Title Affiliation Venue Year Materials
Breaking Secure Aggregation: Label Leakage from Aggregated Gradients in Federated Learning INFOCOM 2024 [PUB]
Strategic Data Revocation in Federated Unlearning INFOCOM 2024 [PUB]
FedTC: Enabling Communication-Efficient Federated Learning via Transform Coding INFOCOM 2024 [PUB]
Federated Learning While Providing Model as a Service: Joint Training and Inference Optimization INFOCOM 2024 [PUB]
FairFed: Improving Fairness and Efficiency of Contribution Evaluation in Federated Learning via Cooperative Shapley Value INFOCOM 2024 [PUB]
DPBalance: Efficient and Fair Privacy Budget Scheduling for Federated Learning as a Service INFOCOM 2024 [PUB]
Tomtit: Hierarchical Federated Fine-Tuning of Giant Models based on Autonomous Synchronization INFOCOM 2024 [PUB]
BR-DeFedRL: Byzantine-Robust Decentralized Federated Reinforcement Learning with Fast Convergence and Communication Efficiency INFOCOM 2024 [PUB]
Titanic: Towards Production Federated Learning with Large Language Models INFOCOM 2024 [PUB]
Expediting In-Network Federated Learning by Voting-Based Consensus Model Compression INFOCOM 2024 [PUB]
Fed-CVLC: Compressing Federated Learning Communications with Variable-Length Codes INFOCOM 2024 [PUB]
Federated Analytics-Empowered Frequent Pattern Mining for Decentralized Web 3.0 Applications INFOCOM 2024 [PUB]
GraphProxy: Communication-Efficient Federated Graph Learning with Adaptive Proxy INFOCOM 2024 [PUB]
Agglomerative Federated Learning: Empowering Larger Model Training via End-Edge-Cloud Collaboration INFOCOM 2024 [PUB] [CODE]
AeroRec: An Efficient On-Device Recommendation Framework using Federated Self-Supervised Knowledge Distillation INFOCOM 2024 [PUB]
Efficient and Straggler-Resistant Homomorphic Encryption for Heterogeneous Federated Learning INFOCOM 2024 [PUB]
Heroes: Lightweight Federated Learning with Neural Composition and Adaptive Local Update in Heterogeneous Edge Networks INFOCOM 2024 [PUB]
Momentum-Based Federated Reinforcement Learning with Interaction and Communication Efficiency INFOCOM 2024 [PUB]
Federated Offline Policy Optimization with Dual Regularization INFOCOM 2024 [PUB]
A Semi-Asynchronous Decentralized Federated Learning Framework via Tree-Graph Blockchain INFOCOM 2024 [PUB]
SpreadFGL: Edge-Client Collaborative Federated Graph Learning with Adaptive Neighbor Generation INFOCOM 2024 [PUB]
Towards Efficient Asynchronous Federated Learning in Heterogeneous Edge Environments INFOCOM 2024 [PUB]
Federated Learning Based Integrated Sensing, Communications, and Powering Over 6G Massive-MIMO Mobile Networks INFOCOM workshop 2024 [PUB]
Decentralized Federated Learning Under Free-riders: Credibility Analysis INFOCOM workshop 2024 [PUB]
TrustBandit: Optimizing Client Selection for Robust Federated Learning Against Poisoning Attacks INFOCOM workshop 2024 [PUB]
Cascade: Enhancing Reinforcement Learning with Curriculum Federated Learning and Interference Avoidance — A Case Study in Adaptive Bitrate Selection INFOCOM workshop 2024 [PUB]
Efficient Adapting for Vision-language Foundation Model in Edge Computing Based on Personalized and Multi-Granularity Federated Learning INFOCOM workshop 2024 [PUB]
Distributed Link Heterogeneity Exploitation for Attention-Weighted Robust Federated Learning in 6G Networks INFOCOM workshop 2024 [PUB]
GAN-Based Privacy Abuse Attack on Federated Learning in IoT Networks INFOCOM workshop 2024 [PUB]
Fedkit: Enabling Cross-Platform Federated Learning for Android and iOS INFOCOM workshop 2024 [PUB] [CODE]
ASR-FED: Agnostic Straggler Resilient Federated Algorithm for Drone Networks Security INFOCOM workshop 2024 [PUB]
Unbiased Federated Learning for Heterogeneous Data Under Unreliable Links INFOCOM workshop 2024 [PUB]
Efficient Client Sampling with Compression in Heterogeneous Federated Learning INFOCOM workshop 2024 [PUB]
Reputation-Aware Scheduling for Secure Internet of Drones: A Federated Multi-Agent Deep Reinforcement Learning Approach INFOCOM workshop 2024 [PUB]
Two-Timescale Energy Optimization for Wireless Federated Learning INFOCOM workshop 2024 [PUB]
A Data Reconstruction Attack Against Vertical Federated Learning Based on Knowledge Transfer INFOCOM workshop 2024 [PUB]
Federated Learning for Energy-efficient Cooperative Perception in Connected and Autonomous Vehicles INFOCOM workshop 2024 [PUB]
Federated Learning-Based Cooperative Model Training for Task-Oriented Semantic Communication INFOCOM workshop 2024 [PUB]
FedBF16-Dynamic: Communication-Efficient Federated Learning with Adaptive Transmission INFOCOM workshop 2024 [PUB]
Designing Robust 6G Networks with Bimodal Distribution for Decentralized Federated Learning INFOCOM workshop 2024 [PUB]
Federated Distributed Deep Reinforcement Learning for Recommendation-enabled Edge Caching INFOCOM workshop 2024 [PUB]
Joint Optimization of Charging Time and Resource Allocation in Wireless Power Transfer Assisted Federated Learning INFOCOM workshop 2024 [PUB]
Joint Client Selection and Privacy Compensation for Differentially Private Federated Learning INFOCOM workshop 2024 [PUB]
Wireless Hierarchical Federated Aggregation Weights Design with Loss-Based-Heterogeneity INFOCOM workshop 2024 [PUB]
ADMarker: A Multi-Modal Federated Learning System for Monitoring Digital Biomarkers of Alzheimer's Disease CUHK MobiCom 2024 [PUB] [PDF] [CODE]
Accelerating the Decentralized Federated Learning via Manipulating Edges SZU WWW 2024 [PUB]
Prompt-enhanced Federated Content Representation Learning for Cross-domain Recommendation SDNU WWW 2024 [PUB] [PDF] [CODE]
PAGE: Equilibrate Personalization and Generalization in Federated Learning XDU WWW 2024 [PUB] [PDF] [CODE]
Federated Learning Vulnerabilities: Privacy Attacks with Denoising Diffusion Probabilistic Models ECNU WWW 2024 [PUB]
Co-clustering for Federated Recommender System UIUC WWW 2024 [PUB]
Incentive and Dynamic Client Selection for Federated Unlearning BUPT WWW 2024 [PUB]
Towards Efficient Communication and Secure Federated Recommendation System via Low-rank Training VinUniversity WWW 2024 [PUB] [PDF] [CODE]
BlockDFL: A Blockchain-based Fully Decentralized Peer-to-Peer Federated Learning Framework ZJU WWW 2024 [PUB] [PDF]
Towards Personalized Privacy: User-Governed Data Contribution for Federated Recommendation UQ WWW 2024 [PUB] [PDF]
FedDSE: Distribution-aware Sub-model Extraction for Federated Learning over Resource-constrained Devices NTU WWW 2024 [PUB]
Cardinality Counting in "Alcatraz": A Privacy-aware Federated Learning Approach CSIRO’s Data61 WWW 2024 [PUB]
Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation BUPT WWW 2024 [PUB] [PDF]
Poisoning Federated Recommender Systems with Fake Users USTC WWW 2024 [PUB] [PDF]
Towards Energy-efficient Federated Learning via INT8-based Training on Mobile DSPs BUPT WWW 2024 [PUB]
Privacy-Preserving and Fairness-Aware Federated Learning for Critical Infrastructure Protection and Resilience UTS WWW 2024 [PUB] [CODE]
When Federated Recommendation Meets Cold-Start Problem: Separating Item Attributes and User Interactions JLU WWW 2024 [PUB] [PDF] [CODE]
How Few Davids Improve One Goliath: Federated Learning in Resource-Skewed Edge Computing Environments UCSD WWW 2024 [PUB] [CODE] [VIDEO]
Poisoning Attack on Federated Knowledge Graph Embedding PolyU WWW 2024 [PUB] [CODE]
FL@FM-TheWebConf'24: International Workshop on Federated Foundation Models for the Web CUHK WWW (Companion Volume) 2024 [PUB] [PAGE]
An Investigation into the Feasibility of Performing Federated Learning on Social Linked Data Servers University of Southampton WWW (Companion Volume) 2024 [PUB]
Exploring Representational Similarity Analysis to Protect Federated Learning from Data Poisoning SYSU WWW (Companion Volume) 2024 [PUB]
Only Send What You Need: Learning to Communicate Efficiently in Federated Multilingual Machine Translation Purdue University WWW (Companion Volume) 2024 [PUB] [PDF]
FedHLT: Efficient Federated Low-Rank Adaption with Hierarchical Language Tree for Multilingual Modeling CUHK WWW (Companion Volume) 2024 [PUB]
HBIAS FedAvg: Smooth Federated Learning Transition for In-use Edge Models IIT WWW (Companion Volume) 2024 [PUB]
Phoenix: A Federated Generative Diffusion Model UW WWW (Companion Volume) 2024 [PUB]
Federated Learning in Large Model Era: Vision-Language Model for Smart City Safety Operation Management ENN; UPC WWW (Companion Volume) 2024 [PUB]
Robust Federated Learning Mitigates Client-side Training Data Distribution Inference Attacks USTC WWW (Companion Volume) 2024 [PUB] [PDF]
GradFilt: Class-wise Targeted Data Reconstruction from Gradients in Federated Learning PolyU WWW (Companion Volume) 2024 [PUB]
Detecting Poisoning Attacks on Federated Learning Using Gradient-Weighted Class Activation Mapping ISEP WWW (Companion Volume) 2024 [PUB]
AutoFed: Heterogeneity-Aware Federated Multimodal Learning for Robust Autonomous Driving NTU MobiCom 2023 [PUB] [PDF]
Efficient Federated Learning for Modern NLP Beiyou Shenzhen Institute MobiCom 2023 [PDF] [解读]
FLASH: Towards a High-performance Hardware Acceleration Architecture for Cross-silo Federated Learning HKUST; Clustar NSDI 2023 [PUB] [SLIDE] [VIDEO]
To Store or Not? Online Data Selection for Federated Learning with Limited Storage. SJTU WWW 2023 [PUB] [PDF]
pFedPrompt: Learning Personalized Prompt for Vision-Language Models in Federated Learning. PolyU WWW 2023 [PUB]
Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding. ZJU; HIC-ZJU WWW 2023 [PUB] [PDF]
Vertical Federated Knowledge Transfer via Representation Distillation for Healthcare Collaboration Networks PKU WWW 2023 [PUB] [PDF] [CODE]
Semi-decentralized Federated Ego Graph Learning for Recommendation SUST WWW 2023 [PUB] [PDF]
FlexiFed: Personalized Federated Learning for Edge Clients with Heterogeneous Model Architectures. Swinburne WWW 2023 [PUB] [CODE]
FedEdge: Accelerating Edge-Assisted Federated Learning. Swinburne WWW 2023 [PUB]
Federated Node Classification over Graphs with Latent Link-type Heterogeneity. Emory University WWW 2023 [PUB] [CODE]
FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection. USTC WWW 2023 [PUB] [PDF] [CODE]
Interaction-level Membership Inference Attack Against Federated Recommender Systems. UQ WWW 2023 [PUB] [PDF]
AgrEvader: Poisoning Membership Inference against Byzantine-robust Federated Learning. Deakin University WWW 2023 [PUB]
Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearning. NJU WWW 2023 [PUB] [PDF] [CODE]
Federated Learning for Metaverse: A Survey. JNU WWW (Companion Volume) 2023 [PUB] [PDF]
Understanding the Impact of Label Skewness and Optimization on Federated Learning for Text Classification KU Leuven WWW (Companion Volume) 2023 [PUB]
Privacy-Preserving Online Content Moderation: A Federated Learning Use Case. CUT WWW (Companion Volume) 2023 [PUB] [PDF]
Privacy-Preserving Online Content Moderation with Federated Learning. CUT WWW (Companion Volume) 2023 [PUB]
A Federated Learning Benchmark for Drug-Target Interaction. University of Turin WWW (Companion Volume) 2023 [PUB] [PDF] [CODE]
Towards a Decentralized Data Hub and Query System for Federated Dynamic Data Spaces. TU Berlin WWW (Companion Volume) 2023 [PUB]
1st Workshop on Federated Learning Technologies1st Workshop on Federated Learning Technologies University of Turin WWW (Companion Volume) 2023 [PUB]
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness and Privacy CUHK WWW (Companion Volume) 2023 [PUB] [PDF]
A Hierarchical Knowledge Transfer Framework for Heterogeneous Federated Learning THU INFOCOM 2023 [PUB]
A Reinforcement Learning Approach for Minimizing Job Completion Time in Clustered Federated Learning Southeast University INFOCOM 2023 [PUB]
Adaptive Configuration for Heterogeneous Participants in Decentralized Federated Learning USTC INFOCOM 2023 [PUB] [PDF]
AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices Guangdong University of Technology INFOCOM 2023 [PUB] [PDF]
AOCC-FL: Federated Learning with Aligned Overlapping via Calibrated Compensation HUST INFOCOM 2023 [PUB]
Asynchronous Federated Unlearning University of Toronto INFOCOM 2023 [PUB] [PDF] [CODE]
Communication-Efficient Federated Learning for Heterogeneous Edge Devices Based on Adaptive Gradient Quantization PSU INFOCOM 2023 [PUB] [PDF]
Enabling Communication-Efficient Federated Learning via Distributed Compressed Sensing Beihang University INFOCOM 2023 [PUB]
Federated Learning under Heterogeneous and Correlated Client Availability Inria INFOCOM 2023 [PUB] [PDF] [CODE]
Federated Learning with Flexible Control IBM INFOCOM 2023 [PUB] [PDF] [CODE]
Federated PCA on Grassmann Manifold for Anomaly Detection in IoT Networks The University of Sydney INFOCOM 2023 [PUB] [PDF]
FedMoS: Taming Client Drift in Federated Learning with Double Momentum and Adaptive Selection HUST INFOCOM 2023 [PUB] [PDF] [CODE]
FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learning NTU INFOCOM 2023 [PUB] [PDF]
Heterogeneity-Aware Federated Learning with Adaptive Client Selection and Gradient Compression USTC INFOCOM 2023
Joint Edge Aggregation and Association for Cost-Efficient Multi-Cell Federated Learning NUDT INFOCOM 2023 [PUB]
Joint Participation Incentive and Network Pricing Design for Federated Learning Northwestern University INFOCOM 2023 [PUB]
More than Enough is Too Much: Adaptive Defenses against Gradient Leakage in Production Federated Learning University of Toronto INFOCOM 2023 [PUB] [PDF] [WEIBO]
Network Adaptive Federated Learning: Congestion and Lossy Compression UTAustin INFOCOM 2023 [PUB] [PDF]
OBLIVION: Poisoning Federated Learning by Inducing Catastrophic Forgetting The Hang Seng University of Hong Kong INFOCOM 2023 [PUB] [CODE]
Privacy as a Resource in Differentially Private Federated Learning BUPT INFOCOM 2023 [PUB]
SplitGP: Achieving Both Generalization and Personalization in Federated Learning KAIST INFOCOM 2023 [PUB] [PDF]
SVDFed: Enabling Communication-Efficient Federated Learning via Singular-Value-Decomposition Beihang University INFOCOM 2023 [PUB]
Tackling System Induced Bias in Federated Learning: Stratification and Convergence Analysis Southern University of Science and Technology INFOCOM 2023 [PUB] [PDF]
Toward Sustainable AI: Federated Learning Demand Response in Cloud-Edge Systems via Auctions BUPT INFOCOM 2023 [PUB] [PDF]
Truthful Incentive Mechanism for Federated Learning with Crowdsourced Data Labeling Auburn University INFOCOM 2023 [PUB] [PDF]
TVFL: Tunable Vertical Federated Learning towards Communication-Efficient Model Serving USTC INFOCOM 2023 [PUB]
PyramidFL: Fine-grained Data and System Heterogeneity-aware Client Selection for Efficient Federated Learning MSU MobiCom 2022 [PUB] [PDF] [CODE]
NestFL: efficient federated learning through progressive model pruning in heterogeneous edge computing pmlabs MobiCom(Poster) 2022 [PUB]
Federated learning-based air quality prediction for smart cities using BGRU model IITM MobiCom(Poster) 2022 [PUB]
FedHD: federated learning with hyperdimensional computing UCSD MobiCom(Demo) 2022 [PUB] [CODE]
Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks Korea University INFOCOM 2022 [PUB]
Towards Optimal Multi-Modal Federated Learning on Non-IID Data with Hierarchical Gradient Blending University of Toronto INFOCOM 2022 [PUB]
Optimal Rate Adaption in Federated Learning with Compressed Communications SZU INFOCOM 2022 [PUB] [PDF]
The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining. CityU INFOCOM 2022 [PUB] [PDF]
Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling. CUHK; AIRS ;Yale University INFOCOM 2022 [PUB] [PDF]
Communication-Efficient Device Scheduling for Federated Learning Using Stochastic Optimization Army Research Laboratory, Adelphi INFOCOM 2022 [PUB] [PDF]
FLASH: Federated Learning for Automated Selection of High-band mmWave Sectors NEU INFOCOM 2022 [PUB] [CODE]
A Profit-Maximizing Model Marketplace with Differentially Private Federated Learning CUHK; AIRS INFOCOM 2022 [PUB]
Protect Privacy from Gradient Leakage Attack in Federated Learning PolyU INFOCOM 2022 [PUB] [SLIDE]
FedFPM: A Unified Federated Analytics Framework for Collaborative Frequent Pattern Mining. SJTU INFOCOM 2022 [PUB] [CODE]
An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning SWJTU;THU WWW 2022 [PUB] [PDF] [CODE]
LocFedMix-SL: Localize, Federate, and Mix for Improved Scalability, Convergence, and Latency in Split Learning Yonsei University WWW 2022 [PUB]
Federated Unlearning via Class-Discriminative Pruning PolyU WWW 2022 [PUB] [PDF] [CODE]
FedKC: Federated Knowledge Composition for Multilingual Natural Language Understanding Purdue WWW 2022 [PUB]
Powering Multi-Task Federated Learning with Competitive GPU Resource Sharing. WWW (Companion Volume) 2022
Federated Bandit: A Gossiping Approach University of California SIGMETRICS 2021 [PUB] [PDF]
Hermes: an efficient federated learning framework for heterogeneous mobile clients Duke University MobiCom 2021 [PUB]
Federated mobile sensing for activity recognition Samsung AI Center MobiCom 2021 [PUB] [PAGE] [TALKS] [VIDEO]
Learning for Learning: Predictive Online Control of Federated Learning with Edge Provisioning. Nanjing University INFOCOM 2021 [PUB]
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation. Purdue INFOCOM 2021 [PUB] [PDF]
FAIR: Quality-Aware Federated Learning with Precise User Incentive and Model Aggregation THU INFOCOM 2021 [PUB]
Sample-level Data Selection for Federated Learning USTC INFOCOM 2021 [PUB]
To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices Xidian University; CAS INFOCOM 2021 [PUB] [PDF]
Cost-Effective Federated Learning Design CUHK; AIRS; Yale University INFOCOM 2021 [PUB] [PDF]
An Incentive Mechanism for Cross-Silo Federated Learning: A Public Goods Perspective The UBC INFOCOM 2021 [PUB]
Resource-Efficient Federated Learning with Hierarchical Aggregation in Edge Computing USTC INFOCOM 2021 [PUB]
FedServing: A Federated Prediction Serving Framework Based on Incentive Mechanism. Jinan University; CityU INFOCOM 2021 [PUB] [PDF]
Federated Learning over Wireless Networks: A Band-limited Coordinated Descent Approach Arizona State University INFOCOM 2021 [PUB] [PDF]
Dual Attention-Based Federated Learning for Wireless Traffic Prediction King Abdullah University of Science and Technology INFOCOM 2021 [PUB] [PDF] [CODE]
FedSens: A Federated Learning Approach for Smart Health Sensing with Class Imbalance in Resource Constrained Edge Computing University of Notre Dame INFOCOM 2021 [PUB]
P-FedAvg: Parallelizing Federated Learning with Theoretical Guarantees SYSU; Guangdong Key Laboratory of Big Data Analysis and Processing INFOCOM 2021 [PUB]
Meta-HAR: Federated Representation Learning for Human Activity Recognition. University of Alberta WWW 2021 [PUB] [PDF] [CODE]
PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization PKU WWW 2021 [PUB] [PDF] [CODE]
Communication Efficient Federated Generalized Tensor Factorization for Collaborative Health Data Analytics Emory WWW 2021 [PUB] [CODE]
Hierarchical Personalized Federated Learning for User Modeling USTC WWW 2021 [PUB]
Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data PKU WWW 2021 [PUB] [PDF] [SLIDE] [CODE]
Incentive Mechanism for Horizontal Federated Learning Based on Reputation and Reverse Auction SYSU WWW 2021 [PUB]
Physical-Layer Arithmetic for Federated Learning in Uplink MU-MIMO Enabled Wireless Networks. Nanjing University INFOCOM 2020 [PUB]
Optimizing Federated Learning on Non-IID Data with Reinforcement Learning 🔥 University of Toronto INFOCOM 2020 [PUB] [SLIDE] [CODE] [解读]
Enabling Execution Assurance of Federated Learning at Untrusted Participants THU INFOCOM 2020 [PUB] [CODE]
Billion-scale federated learning on mobile clients: a submodel design with tunable privacy SJTU MobiCom 2020 [PUB]
Federated Learning over Wireless Networks: Optimization Model Design and Analysis The University of Sydney INFOCOM 2019 [PUB] [CODE]
Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning Wuhan University INFOCOM 2019 [PUB] [PDF] [UC.]
InPrivate Digging: Enabling Tree-based Distributed Data Mining with Differential Privacy Collaborative Innovation Center of Geospatial Technology INFOCOM 2018 [PUB]

fl in top system conference and journal

Federated Learning papers accepted by top Database conference and journal, including OSDI(USENIX Symposium on Operating Systems Design and Implementation), SOSP(Symposium on Operating Systems Principles), ISCA(International Symposium on Computer Architecture), MLSys(Conference on Machine Learning and Systems), EuroSys(European Conference on Computer Systems), TPDS(IEEE Transactions on Parallel and Distributed Systems), DAC(Design Automation Conference), TOCS(ACM Transactions on Computer Systems), TOS(ACM Transactions on Storage), TCAD(IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems), TC(IEEE Transactions on Computers).

fl in top system conference and journal
Title Affiliation Venue Year Materials
AdaptiveFL: Adaptive Heterogeneous Federated Learning for Resource-Constrained AIoT Systems. DAC 2024 [PUB]
Fake Node-Based Perception Poisoning Attacks against Federated Object Detection Learning in Mobile Computing Networks DAC 2024 [PUB]
Flagger: Cooperative Acceleration for Large-Scale Cross-Silo Federated Learning Aggregation ISCA 2024 [PUB]
FedTrans: Efficient Federated Learning via Multi-Model Transformation UIUC MLSys 2024 [PUB] [PDF]
LIFL: A Lightweight, Event-driven Serverless Platform for Federated Learning UC Riverside MLSys 2024 [PUB] [PDF]
HeteroSwitch: Characterizing and Taming System-Induced Data Heterogeneity in Federated Learning Korea University MLSys 2024 [PUB] [PDF] [CODE]
DeTA: Minimizing Data Leaks in Federated Learning via Decentralized and Trustworthy Aggregation IBM Research EuroSys 2024 [PUB]
FLOAT: Federated Learning Optimizations with Automated Tuning Virginia Tech EuroSys 2024 [PUB] [CODE]
Totoro: A Scalable Federated Learning Engine for the Edge UCSC EuroSys 2024 [PUB]
Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy HKUST EuroSys 2024 [PUB] [PDF] [CODE]
FLIGAN: Enhancing Federated Learning with Incomplete Data using GAN EuroSys workshop 2024 [PUB]
ALS Algorithm for Robust and Communication-Efficient Federated Learning EuroSys workshop 2024 [PUB]
FedRDMA: Communication-Efficient Cross-Silo Federated LLM via Chunked RDMA Transmission. EuroSys workshop 2024 [PUB]
Breaking the Memory Wall for Heterogeneous Federated Learning via Model Splitting. TPDS 2024 [PUB]
SR-FDIL: Synergistic Replay for Federated Domain-Incremental Learning TPDS 2024 [PUB]
FedVeca: Federated Vectorized Averaging on Non-IID Data With Adaptive Bi-Directional Global Objective TPDS 2024 [PUB]
Trusted Model Aggregation With Zero-Knowledge Proofs in Federated Learning. TPDS 2024 [PUB]
Accelerating Communication-Efficient Federated Multi-Task Learning With Personalization and Fairness. TPDS 2024 [PUB]
Privacy-Preserving Data Selection for Horizontal and Vertical Federated Learning. TPDS 2024 [PUB]
High-Performance Hardware Acceleration Architecture for Cross-Silo Federated Learning TPDS 2024 [PUB]
Joint Participant and Learning Topology Selection for Federated Learning in Edge Clouds TPDS 2024 [PUB]
Synchronize Only the Immature Parameters: Communication-Efficient Federated Learning By Freezing Parameters Adaptively SJTU TPDS 2024 [PUB]
FedREM: Guided Federated Learning in the Presence of Dynamic Device Unpredictability SYSU TPDS 2024 [PUB]
Fed-RAC: Resource-Aware Clustering for Tackling Heterogeneity of Participants in Federated Learning IITP TPDS 2024 [PUB] [PDF]
Taking Advantage of the Mistakes: Rethinking Clustered Federated Learning for IoT Anomaly Detection UVIC TPDS 2024 [PUB]
FedICT: Federated Multi-Task Distillation for Multi-Access Edge Computing UCAS TPDS 2024 [PUB] [PDF]
Collaboration in Federated Learning With Differential Privacy: A Stackelberg Game Analysis SYSU TPDS 2024 [PUB]
FAST: Enhancing Federated Learning Through Adaptive Data Sampling and Local Training USTC TPDS 2024 [PUB]
EcoFed: Efficient Communication for DNN Partitioning-Based Federated Learning University of St Andrews TPDS 2024 [PUB] [PDF] [CODE]
FedHAP: Federated Hashing With Global Prototypes for Cross-Silo Retrieval THU TPDS 2024 [PUB] [PDF]
FlexFL: Heterogeneous Federated Learning via APoZ-Guided Flexible Pruning in Uncertain Scenarios. TCAD 2024 [PUB]
Personalized Meta-Federated Learning for IoT-Enabled Health Monitoring TCAD 2024 [PUB]
NebulaFL: Self-Organizing Efficient Multilayer Federated Learning Framework With Adaptive Load Tuning in Heterogeneous Edge Systems TCAD 2024 [PUB]
CaBaFL: Asynchronous Federated Learning via Hierarchical Cache and Feature Balance TCAD 2024 [PUB]
FedStar: Efficient Federated Learning on Heterogeneous Communication Networks USTC TCAD 2024 [PUB]
Lithography Hotspot Detection Based on Heterogeneous Federated Learning With Local Adaptation and Feature Selection ZJU TCAD 2024 [PUB] [PDF]
FedComp: A Federated Learning Compression Framework for Resource-Constrained Edge Computing Devices HIT TCAD 2024 [PUB]
BSR-FL: An Efficient Byzantine-Robust Privacy-Preserving Federated Learning Framework TC 2024 [PUB]
User-Distribution-Aware Federated Learning for Efficient Communication and Fast Inference ECNU; SHU TC 2024 [PUB]
FedRFQ: Prototype-Based Federated Learning With Reduced Redundancy, Minimal Failure, and Enhanced Quality SDU TC 2024 [PUB] [PDF]
Value of Information: A Comprehensive Metric for Client Selection in Federated Edge Learning SDU TC 2024 [PUB]
Age-Aware Data Selection and Aggregator Placement for Timely Federated Continual Learning in Mobile Edge Computing DLUT TC 2024 [PUB]
FedGKD: Toward Heterogeneous Federated Learning via Global Knowledge Distillation HUST TC 2024 [PUB] [PDF]
Digital Twin-Assisted Federated Learning Service Provisioning Over Mobile Edge Networks SDU TC 2024 [PUB]
REFL: Resource-Efficient Federated Learning QMUL EuroSys 2023 [PUB] [PDF] [CODE]
A First Look at the Impact of Distillation Hyper-Parameters in Federated Knowledge Distillation EuroSys workshop 2023 [PUB]
Towards Practical Few-shot Federated NLP EuroSys workshop 2023 [PUB]
Can Fair Federated Learning Reduce the need for Personalisation? EuroSys workshop 2023 [PUB]
Gradient-less Federated Gradient Boosting Tree with Learnable Learning Rates EuroSys workshop 2023 [PUB]
Towards Robust and Bias-free Federated Learning EuroSys workshop 2023 [PUB]
FedTree: A Federated Learning System For Trees UC Berkeley MLSys 2023 [PUB] [CODE]
FLINT: A Platform for Federated Learning Integration LinkedIn MLSys 2023 [PUB] [PDF]
On Noisy Evaluation in Federated Hyperparameter Tuning CMU MLSys 2023 [PUB] [PDF] [CODE]
GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning UBC MLSys 2023 [PUB] [PDF] [CODE]
Self-Supervised On-Device Federated Learning From Unlabeled Streams. FDU TCAD 2023 [PUB] [PDF]
Optimizing Training Efficiency and Cost of Hierarchical Federated Learning in Heterogeneous Mobile-Edge Cloud Computing ECNU TCAD 2023 [PUB]
Lightweight Blockchain-Empowered Secure and Efficient Federated Edge Learning University of Exeter TC 2023 [PUB]
Towards Data-Independent Knowledge Transfer in Model-Heterogeneous Federated Learning PolyU TC 2023 [PUB]
A New Federated Scheduling Algorithm for Arbitrary-Deadline DAG Tasks NEFU TC 2023 [PUB]
Privacy-Enhanced Decentralized Federated Learning at Dynamic Edge SDU TC 2023 [PUB]
Byzantine-Resilient Federated Learning at Edge SDU TC 2023 [PUB] [PDF]
PrivAim: A Dual-Privacy Preserving and Quality-Aware Incentive Mechanism for Federated Learning CSU TC 2023 [PUB]
Accelerating Federated Learning With a Global Biased Optimiser University of Exeter TC 2023 [PUB] [PDF] [CODE]
Type-Aware Federated Scheduling for Typed DAG Tasks on Heterogeneous Multicore Platforms TU Dortmund University TC 2023 [PUB] [CODE]
Sandbox Computing: A Data Privacy Trusted Sharing Paradigm Via Blockchain and Federated Learning. BUPT TC 2023 [PUB]
CHEESE: Distributed Clustering-Based Hybrid Federated Split Learning Over Edge Networks SUDA TPDS 2023 [PUB]
Hierarchical Federated Learning With Momentum Acceleration in Multi-Tier Networks University of Sydney TPDS 2023 [PUB] [PDF]
Dap-FL: Federated Learning Flourishes by Adaptive Tuning and Secure Aggregation Xidian University TPDS 2023 [PUB] [PDF] [CODE]
Collaborative Intrusion Detection System for SDVN: A Fairness Federated Deep Learning Approach Anhui University TPDS 2023 [PUB]
Energy-Aware, Device-to-Device Assisted Federated Learning in Edge Computing ANU TPDS 2023 [PUB]
Faster Federated Learning With Decaying Number of Local SGD Steps University of Exeter TPDS 2023 [PUB] [PDF] [CODE]
DRFL: Federated Learning in Diabetic Retinopathy Grading Using Fundus Images National Institute of Technology Silchar TPDS 2023 [PUB]
FedProf: Selective Federated Learning Based on Distributional Representation Profiling Peng Cheng Laboratory TPDS 2023 [PUB] [PDF] [UC]
Federated Ensemble Model-Based Reinforcement Learning in Edge Computing University of Exeter TPDS 2023 [PUB] [PDF]
Incentive Mechanism Design for Joint Resource Allocation in Blockchain-Based Federated Learning. IUPUI TPDS 2023 [PUB] [PDF]
HiFlash: Communication-Efficient Hierarchical Federated Learning With Adaptive Staleness Control and Heterogeneity-Aware Client-Edge Association. SYSU TPDS 2023 [PUB] [PDF]
From Deterioration to Acceleration: A Calibration Approach to Rehabilitating Step Asynchronism in Federated Optimization. PolyU TPDS 2023 [PUB] [PDF] [CODE]
Federated Learning Over Coupled Graphs XJTU TPDS 2023 [PUB] [PDF]
Privacy vs. Efficiency: Achieving Both Through Adaptive Hierarchical Federated Learning NUDT TPDS 2023 [PUB]
On Model Transmission Strategies in Federated Learning With Lossy Communications SZU TPDS 2023 [PUB]
Scheduling Algorithms for Federated Learning With Minimal Energy Consumption University of Bordeaux TPDS 2023 [PUB] [PDF] [CODE]
Auction-Based Cluster Federated Learning in Mobile Edge Computing Systems HIT TPDS 2023 [PUB] [PDF]
Personalized Edge Intelligence via Federated Self-Knowledge Distillation. HUST TPDS 2023 [PUB] [CODE]
Design of a Quantization-Based DNN Delta Compression Framework for Model Snapshots and Federated Learning. HIT TPDS 2023 [PUB]
Multi-Job Intelligent Scheduling With Cross-Device Federated Learning. Baidu TPDS 2023 [PUB] [PDF]
Data-Centric Client Selection for Federated Learning Over Distributed Edge Networks. IIT TPDS 2023 [PUB]
GossipFL: A Decentralized Federated Learning Framework With Sparsified and Adaptive Communication. HKBU TPDS 2023 [PUB]
FedMDS: An Efficient Model Discrepancy-Aware Semi-Asynchronous Clustered Federated Learning Framework. CQU TPDS 2023 [PUB]
HierFedML: Aggregator Placement and UE Assignment for Hierarchical Federated Learning in Mobile Edge Computing. DUT TPDS 2023 [PUB]
Data selection for efficient model update in federated learning EuroSys workshop 2022 [PUB]
Empirical analysis of federated learning in heterogeneous environments EuroSys workshop 2022 [PUB]
BAFL: A Blockchain-Based Asynchronous Federated Learning Framework TC 2022 [PUB] [CODE]
L4L: Experience-Driven Computational Resource Control in Federated Learning TC 2022 [PUB]
Adaptive Federated Learning on Non-IID Data With Resource Constraint TC 2022 [PUB]
Locking Protocols for Parallel Real-Time Tasks With Semaphores Under Federated Scheduling. TCAD 2022 [PUB]
Client Scheduling and Resource Management for Efficient Training in Heterogeneous IoT-Edge Federated Learning ECNU TCAD 2022 [PUB]
PervasiveFL: Pervasive Federated Learning for Heterogeneous IoT Systems. ECNU TCAD 2022 [PUB]
FHDnn: communication efficient and robust federated learning for AIoT networks UC San Diego DAC 2022 [PUB]
A Decentralized Federated Learning Framework via Committee Mechanism With Convergence Guarantee SYSU TPDS 2022 [PUB] [PDF]
Improving Federated Learning With Quality-Aware User Incentive and Auto-Weighted Model Aggregation THU TPDS 2022 [PUB]
$f$funcX: Federated Function as a Service for Science. SUST TPDS 2022 [PUB] [PDF]
Blockchain Assisted Decentralized Federated Learning (BLADE-FL): Performance Analysis and Resource Allocation NUST TPDS 2022 [PUB] [PDF] [CODE]
Adaptive Federated Deep Reinforcement Learning for Proactive Content Caching in Edge Computing. CQU TPDS 2022 [PUB]
TDFL: Truth Discovery Based Byzantine Robust Federated Learning BIT TPDS 2022 [PUB]
Federated Learning With Nesterov Accelerated Gradient The University of Sydney TPDS 2022 [PUB] [PDF]
FedGraph: Federated Graph Learning with Intelligent Sampling UoA TPDS 2022 [PUB] [CODE] [解读]
AUCTION: Automated and Quality-Aware Client Selection Framework for Efficient Federated Learning. THU TPDS 2022 [PUB]
DONE: Distributed Approximate Newton-type Method for Federated Edge Learning. University of Sydney TPDS 2022 [PUB] [PDF] [CODE]
Flexible Clustered Federated Learning for Client-Level Data Distribution Shift. CQU TPDS 2022 [PUB] [PDF] [CODE]
Min-Max Cost Optimization for Efficient Hierarchical Federated Learning in Wireless Edge Networks. Xidian University TPDS 2022 [PUB]
LightFed: An Efficient and Secure Federated Edge Learning System on Model Splitting. CSU TPDS 2022 [PUB]
On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Federated Learning. Purdue TPDS 2022 [PUB] [PDF] [CODE]
Incentive-Aware Autonomous Client Participation in Federated Learning. Sun Yat-sen University TPDS 2022 [PUB]
Communicational and Computational Efficient Federated Domain Adaptation. HKUST TPDS 2022 [PUB]
Decentralized Edge Intelligence: A Dynamic Resource Allocation Framework for Hierarchical Federated Learning. NTU TPDS 2022 [PUB]
Differentially Private Byzantine-Robust Federated Learning. Qufu Normal University TPDS 2022 [PUB]
Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing. University of Exeter TPDS 2022 [PUB] [PDF] [CODE]
Reputation-Aware Hedonic Coalition Formation for Efficient Serverless Hierarchical Federated Learning. BUAA TPDS 2022 [PUB]
Differentially Private Federated Temporal Difference Learning. Stony Brook University TPDS 2022 [PUB]
Towards Efficient and Stable K-Asynchronous Federated Learning With Unbounded Stale Gradients on Non-IID Data. XJTU TPDS 2022 [PUB] [PDF]
Communication-Efficient Federated Learning With Compensated Overlap-FedAvg. SCU TPDS 2022 [PUB] [PDF] [CODE]
PAPAYA: Practical, Private, and Scalable Federated Learning. Meta AI MLSys 2022 [PUB] [PDF]
LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation in Federated Learning USC MLSys 2022 [PUB] [PDF] [CODE]
Accelerated Training via Device Similarity in Federated Learning EuroSys workshop 2021 [PUB]
Towards Federated Learning with Attention Transfer to Mitigate System and Data Heterogeneity of Clients EuroSys workshop 2021 [PUB]
Towards Mitigating Device Heterogeneity in Federated Learning via Adaptive Model Quantization EuroSys workshop 2021 [PUB]
SAFA: A Semi-Asynchronous Protocol for Fast Federated Learning With Low Overhead University of Warwick TC 2021 [PDF] [PUB] [CODE]
Efficient Federated Learning for Cloud-Based AIoT Applications ECNU TCAD 2021 [PUB]
HADFL: Heterogeneity-aware Decentralized Federated Learning Framework USTC DAC 2021 [PDF] [PUB]
Helios: Heterogeneity-Aware Federated Learning with Dynamically Balanced Collaboration. GMU DAC 2021 [PDF] [PUB]
FedLight: Federated Reinforcement Learning for Autonomous Multi-Intersection Traffic Signal Control. ECNU DAC 2021 [PUB]
Oort: Efficient Federated Learning via Guided Participant Selection University of Michigan OSDI 2021 [PUB] [PDF] [CODE] [SLIDES] [VIDEO]
Towards Efficient Scheduling of Federated Mobile Devices Under Computational and Statistical Heterogeneity. Old Dominion University TPDS 2021 [PUB] [PDF]
Self-Balancing Federated Learning With Global Imbalanced Data in Mobile Systems. CQU TPDS 2021 [PUB] [CODE]
An Efficiency-Boosting Client Selection Scheme for Federated Learning With Fairness Guarantee SCUT TPDS 2021 [PUB] [PDF] [解读]
Proof of Federated Learning: A Novel Energy-Recycling Consensus Algorithm. Beijing Normal University TPDS 2021 [PUB] [PDF]
Biscotti: A Blockchain System for Private and Secure Federated Learning. UBC TPDS 2021 [PUB]
Mutual Information Driven Federated Learning. Deakin University TPDS 2021 [PUB]
Accelerating Federated Learning Over Reliability-Agnostic Clients in Mobile Edge Computing Systems. University of Warwick TPDS 2021 [PUB] [PDF]
FedSCR: Structure-Based Communication Reduction for Federated Learning. HKU TPDS 2021 [PUB]
FedScale: Benchmarking Model and System Performance of Federated Learning 🔥 University of Michigan SOSP workshop / ICML 2022 2021 [PUB] [PDF] [CODE] [解读]
Redundancy in cost functions for Byzantine fault-tolerant federated learning SOSP workshop 2021 [PUB]
Towards an Efficient System for Differentially-private, Cross-device Federated Learning SOSP workshop 2021 [PUB]
GradSec: a TEE-based Scheme Against Federated Learning Inference Attacks SOSP workshop 2021 [PUB]
Community-Structured Decentralized Learning for Resilient EI. SOSP workshop 2021 [PUB]
Separation of Powers in Federated Learning (Poster Paper) IBM Research SOSP workshop 2021 [PUB] [PDF]
Towards federated unsupervised representation learning EuroSys workshop 2020 [PUB]
CoLearn: enabling federated learning in MUD-compliant IoT edge networks EuroSys workshop 2020 [PUB]
LDP-Fed: federated learning with local differential privacy. EuroSys workshop 2020 [PUB]
Accelerating Federated Learning via Momentum Gradient Descent. USTC TPDS 2020 [PUB] [PDF]
Towards Fair and Privacy-Preserving Federated Deep Models. NUS TPDS 2020 [PUB] [PDF] [CODE]
Federated Optimization in Heterogeneous Networks 🔥 CMU MLSys 2020 [PUB] [PDF] [CODE]
Towards Federated Learning at Scale: System Design Google MLSys 2019 [PUB] [PDF] [解读]

fl in top conference and journal other fields

Federated Learning papers accepted by top conference and journal in the other fields, including ICSE(International Conference on Software Engineering), FOCS(IEEE Annual Symposium on Foundations of Computer Science), STOC(Symposium on the Theory of Computing).

fl in top conference and journal other fields
Title Affiliation Venue Year Materials
F-CodeLLM: A Federated Learning Framework for Adapting Large Language Models to Practical Software Development SYSU ICSE Companion 2024 PUB
Raft Protocol for Fault Tolerance and Self-Recovery in Federated Learning SINTEF Digital SEAMS@ICSE 2024 PUB
FedDebug: Systematic Debugging for Federated Learning Applications. Virginia Tech ICSE 2023 pub pdf code
FedSlice: Protecting Federated Learning Models from Malicious Participants with Model Slicing. PKU ICSE 2023 pub code
Towards a Self-Adaptive Architecture for Federated Learning of Industrial Automation Systems SEAMS@ICSE workshop 2021 pub
Federated Machine Learning as a Self-Adaptive Problem SEAMS@ICSE workshop 2021 pub

fl on graph data and graph neural networks

dblp

This section partially refers to DBLP search engine and repositories Awesome-Federated-Learning-on-Graph-and-GNN-papers and Awesome-Federated-Machine-Learning.

fl on graph data and graph neural networks
Title Affiliation Venue Year Materials
FedGCN: Convergence and Communication Tradeoffs in Federated Training of Graph Convolutional Networks CMU NeurIPS 🎓 2023 [PDF] [CODE]
Wyze Rule: Federated Rule Dataset for Rule Recommendation Benchmarking CMU NeurIPS Dataset Track 🎓 2023 [PDF] [DATASET] [CODE]
Federated Visualization: A Privacy-Preserving Strategy for Aggregated Visual Query. ZJU IEEE Trans. Vis. Comput. Graph. 🎓 2023 [PUB] [PDF]
Personalized Subgraph Federated Learning KAIST ICML 🎓 2023 [PDF]
Semi-decentralized Federated Ego Graph Learning for Recommendation SUST WWW:mortar_board: 2023 [PUB] [PDF]
Federated Graph Neural Network for Fast Anomaly Detection in Controller Area Networks ECUST IEEE Trans. Inf. Forensics Secur. 🎓 2023 [PUB]
Federated Learning Over Coupled Graphs XJTU IEEE Trans. Parallel Distributed Syst. 🎓 2023 [PUB] [PDF]
HetVis: A Visual Analysis Approach for Identifying Data Heterogeneity in Horizontal Federated Learning Nankai University IEEE Trans. Vis. Comput. Graph. 🎓 2023 [PUB] [PDF]
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing UTS AAAI 🎓 2023 [PDF] [CODE]
FedGS: Federated Graph-based Sampling with Arbitrary Client Availability XMU AAAI 🎓 2023 [PDF] [CODE]
An Information Theoretic Perspective for Heterogeneous Subgraph Federated Learning. PKU DASFAA 2023 [PUB]
GraphCS: Graph-based client selection for heterogeneity in federated learning NUDT J. Parallel Distributed Comput. 2023 [PUB]
Towards On-Device Federated Learning: A Direct Acyclic Graph-based Blockchain Approach BUPT IEEE Trans. Neural Networks Learn. Syst. 2023 [PUB] [PDF]
Short-Term Traffic Flow Prediction Based on Graph Convolutional Networks and Federated Learning ZUEL IEEE Trans. Intell. Transp. Syst. 2023 [PUB]
Hyper-Graph Attention Based Federated Learning Methods for Use in Mental Health Detection. HVL IEEE J. Biomed. Health Informatics 2023 [PUB]
Federated Learning-Based Cross-Enterprise Recommendation With Graph Neural IEEE Trans. Ind. Informatics 2023 [PUB]
Graph-Fraudster: Adversarial Attacks on Graph Neural Network Based Vertical Federated Learning ZJUT IEEE Trans. Comput. Soc. Syst. 2023 [PUB] [PDF] [CODE]
ESA-FedGNN: Efficient secure aggregation for federated graph neural networks. Peer Peer Netw. Appl. 2023 [PUB]
FedCKE: Cross-Domain Knowledge Graph Embedding in Federated Learning SWJTU IEEE Trans. Big Data 2023 [PUB]
Asynchronous federated learning with directed acyclic graph-based blockchain in edge computing: Overview, design, and challenges. Expert Syst. Appl. 2023 [PUB]
FedGR: Federated Graph Neural Network for Recommendation System CUPT Axioms 2023 [PUB]
S-Glint: Secure Federated Graph Learning With Traffic Throttling and Flow Scheduling. IEEE Trans. Green Commun. Netw. 2023 [PUB]
FedAGCN: A traffic flow prediction framework based on federated learning and Asynchronous Graph Convolutional Network Appl. Soft Comput. 2023 [PUB]
GDFed: Dynamic Federated Learning for Heterogenous Device Using Graph Neural Network KHU ICOIN 2023 [PUB] [CODE]
Coordinated Scheduling and Decentralized Federated Learning Using Conflict Clustering Graphs in Fog-Assisted IoD Networks UBC IEEE Trans. Veh. Technol. 2023 [PUB]
FedRule: Federated Rule Recommendation System with Graph Neural Networks CMU IoTDI 2023 [PUB] [PDF] [CODE]
FedWalk: Communication Efficient Federated Unsupervised Node Embedding with Differential Privacy SJTU KDD 🎓 2022 [PUB] [PDF]
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Platform for Federated Graph Learning 🔥 Alibaba KDD (Best Paper Award) 🎓 2022 [PDF] [CODE] [PUB]
Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning SJTU ICML 🎓 2022 [PUB] [CODE]
Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting kg. ZJU IJCAI 🎓 2022 [PUB] [PDF] [CODE]
Personalized Federated Learning With a Graph UTS IJCAI 🎓 2022 [PUB] [PDF] [CODE]
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification ZJU IJCAI 🎓 2022 [PUB] [PDF]
SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data USC AAAI:mortar_board: 2022 [PUB] [PDF] [CODE] [解读]
FedGraph: Federated Graph Learning with Intelligent Sampling UoA TPDS 🎓 2022 [PUB] [CODE] [解读]
Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications surv. University of Virginia SIGKDD Explor. 2022 [PUB] [PDF]
Semantic Vectorization: Text- and Graph-Based Models. IBM Research Federated Learning 2022 [PUB]
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs IIT ICDM 2022 [PUB] [PDF] [解读]
More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks TU Delft ACSAC 2022 [PUB] [PDF]
FedNI: Federated Graph Learning with Network Inpainting for Population-Based Disease Prediction UESTC TMI 2022 [PUB] [PDF]
SemiGraphFL: Semi-supervised Graph Federated Learning for Graph Classification. PKU PPSN 2022 [PUB]
Federated Spatio-Temporal Traffic Flow Prediction Based on Graph Convolutional Network TJU WCSP 2022 [PUB]
A federated graph neural network framework for privacy-preserving personalization THU Nature Communications 2022 [PUB] [CODE] [解读]
Malicious Transaction Identification in Digital Currency via Federated Graph Deep Learning BIT INFOCOM Workshops 2022 [PUB]
Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation kg. Lehigh University EMNLP 2022 [PUB] [PDF] [CODE]
Power Allocation for Wireless Federated Learning using Graph Neural Networks Rice University ICASSP 2022 [PUB] [PDF] [CODE]
Privacy-Preserving Federated Multi-Task Linear Regression: A One-Shot Linear Mixing Approach Inspired By Graph Regularization UC ICASSP 2022 [PUB] [PDF] [CODE]
Graph-regularized federated learning with shareable side information NWPU Knowl. Based Syst. 2022 [PUB]
Federated knowledge graph completion via embedding-contrastive learning kg. ZJU Knowl. Based Syst. 2022 [PUB]
Federated Graph Learning with Periodic Neighbour Sampling HKU IWQoS 2022 [PUB]
FedGSL: Federated Graph Structure Learning for Local Subgraph Augmentation. Big Data 2022 [PUB]
Domain-Aware Federated Social Bot Detection with Multi-Relational Graph Neural Networks. UCAS; CAS IJCNN 2022 [PUB]
A Federated Multi-Server Knowledge Graph Embedding Framework For Link Prediction. ICTAI 2022 [PUB]
A Privacy-Preserving Subgraph-Level Federated Graph Neural Network via Differential Privacy Ping An Technology KSEM 2022 [PUB] [PDF]
Clustered Graph Federated Personalized Learning. NTNU IEEECONF 2022 [PUB]
Investigating the Predictive Reproducibility of Federated Graph Neural Networks using Medical Datasets. MICCAI Workshop 2022 [PDF] [CODE]
Peer-to-Peer Variational Federated Learning Over Arbitrary Graphs UCSD Int. J. Bio Inspired Comput. 2022 [PUB]
Federated Multi-task Graph Learning ZJU ACM Trans. Intell. Syst. Technol. 2022 [PUB]
Graph-Based Traffic Forecasting via Communication-Efficient Federated Learning SUSTech WCNC 2022 [PUB]
Federated meta-learning for spatial-temporal prediction NEU Neural Comput. Appl. 2022 [PUB] [CODE]
BiG-Fed: Bilevel Optimization Enhanced Graph-Aided Federated Learning NTU IEEE Transactions on Big Data 2022 [PUB] [PDF]
Leveraging Spanning Tree to Detect Colluding Attackers in Federated Learning Missouri S&T INFCOM Workshops 2022 [PUB]
Federated learning of molecular properties with graph neural networks in a heterogeneous setting University of Rochester Patterns 2022 [PUB] [PDF] [CODE]
Graph Federated Learning for CIoT Devices in Smart Home Applications University of Toronto IEEE Internet Things J. 2022 [PUB] [PDF] [CODE]
Multi-Level Federated Graph Learning and Self-Attention Based Personalized Wi-Fi Indoor Fingerprint Localization SYSU IEEE Commun. Lett. 2022 [PUB]
Graph-Assisted Communication-Efficient Ensemble Federated Learning UC EUSIPCO 2022 [PUB] [PDF]
Decentralized Graph Federated Multitask Learning for Streaming Data NTNU CISS 2022 [PUB]
Neural graph collaborative filtering for privacy preservation based on federated transfer learning Electron. Libr. 2022 [PUB]
Dynamic Neural Graphs Based Federated Reptile for Semi-Supervised Multi-Tasking in Healthcare Applications Oxford JBHI 2022 [PUB]
FedGCN: Federated Learning-Based Graph Convolutional Networks for Non-Euclidean Spatial Data NUIST Mathematics 2022 [PUB]
Federated Dynamic Graph Neural Networks with Secure Aggregation for Video-based Distributed Surveillance ND ACM Trans. Intell. Syst. Technol. 2022 [PUB] [PDF] [解读]
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation. Purdue INFOCOM 🎓 2021 [PUB] [PDF]
Federated Graph Classification over Non-IID Graphs Emory NeurIPS 🎓 2021 [PUB] [PDF] [CODE] [解读]
Subgraph Federated Learning with Missing Neighbor Generation Emory; UBC; Lehigh University NeurIPS 🎓 2021 [PUB] [PDF]
Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling USC KDD 🎓 2021 [PUB] [PDF] [CODE] [解读]
Differentially Private Federated Knowledge Graphs Embedding kg. BUAA CIKM 2021 [PUB] [PDF] [CODE] [解读]
Decentralized Federated Graph Neural Networks Blue Elephant Tech IJCAI Workshop 2021 [PDF]
FedSGC: Federated Simple Graph Convolution for Node Classification HKUST IJCAI Workshop 2021 [PDF]
FL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery: Special Session Paper UNM ICCAD 2021 [PUB]
FASTGNN: A Topological Information Protected Federated Learning Approach for Traffic Speed Forecasting UTS IEEE Trans. Ind. Informatics 2021 [PUB]
DAG-FL: Direct Acyclic Graph-based Blockchain Empowers On-Device Federated Learning BUPT; UESTC ICC 2021 [PUB] [PDF]
FedE: Embedding Knowledge Graphs in Federated Setting kg. ZJU IJCKG 2021 [PUB] [PDF] [CODE]
Federated Knowledge Graph Embeddings with Heterogeneous Data kg. TJU CCKS 2021 [PUB]
A Graph Federated Architecture with Privacy Preserving Learning EPFL SPAWC 2021 [PUB] [PDF] [解读]
Federated Social Recommendation with Graph Neural Network UIC ACM TIST 2021 [PUB] [PDF] [CODE]
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks 🔥 surv. USC ICLR Workshop / MLSys Workshop 2021 [PDF] [CODE] [解读]
A Federated Multigraph Integration Approach for Connectional Brain Template Learning Istanbul Technical University MICCAI Workshop 2021 [PUB] [CODE]
Cluster-driven Graph Federated Learning over Multiple Domains Politecnico di Torino CVPR Workshop 2021 [PDF] [解读]
FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation THU ICML workshop 2021 [PDF] [解读]
Decentralized federated learning of deep neural networks on non-iid data RISE; Chalmers University of Technology ICML workshop 2021 [PDF] [CODE]
Glint: Decentralized Federated Graph Learning with Traffic Throttling and Flow Scheduling The University of Aizu IWQoS 2021 [PUB]
Federated Graph Neural Network for Cross-graph Node Classification BUPT CCIS 2021 [PUB]
GraFeHTy: Graph Neural Network using Federated Learning for Human Activity Recognition Lead Data Scientist Ericsson Digital Services ICMLA 2021 [PUB]
Distributed Training of Graph Convolutional Networks Sapienza University of Rome TSIPN 2021 [PUB] [PDF] [解读]
Decentralized federated learning for electronic health records UMN NeurIPS Workshop / CISS 2020 [PUB] [PDF] [解读]
ASFGNN: Automated Separated-Federated Graph Neural Network Ant Group PPNA 2020 [PUB] [PDF] [解读]
Decentralized federated learning via sgd over wireless d2d networks SZU SPAWC 2020 [PUB] [PDF]
SGNN: A Graph Neural Network Based Federated Learning Approach by Hiding Structure SDU BigData 2019 [PUB] [PDF]
Towards Federated Graph Learning for Collaborative Financial Crimes Detection IBM NeurIPS Workshop 2019 [PDF]
Federated learning of predictive models from federated Electronic Health Records ⭐ BU Int. J. Medical Informatics 2018 [PUB]
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks. preprint 2023 [PDF] [CODE]
Graph-guided Personalization for Federated Recommendation. preprint 2023 [PDF]
GraphGANFed: A Federated Generative Framework for Graph-Structured Molecules Towards Efficient Drug Discovery. preprint 2023 [PDF]
GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data preprint 2023 [PDF]
Vertical Federated Graph Neural Network for Recommender System preprint 2023 [PDF] [CODE]
Lumos: Heterogeneity-aware Federated Graph Learning over Decentralized Devices preprint 2023 [PDF]
Securing IoT Communication using Physical Sensor Data - Graph Layer Security with Federated Multi-Agent Deep Reinforcement Learning. preprint 2023 [PDF]
Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearning. preprint 2023 [PDF]
Uplink Scheduling in Federated Learning: an Importance-Aware Approach via Graph Representation Learning preprint 2023 [PDF]
Graph Federated Learning with Hidden Representation Sharing UCLA preprint 2022 [PDF]
M3FGM:a node masking and multi-granularity message passing-based federated graph model for spatial-temporal data prediction Xidian University preprint 2022 [PDF]
Federated Graph-based Networks with Shared Embedding BUCEA preprint 2022 [PDF]
Privacy-preserving Decentralized Federated Learning over Time-varying Communication Graph Lancaster University preprint 2022 [PDF]
Heterogeneous Federated Learning on a Graph. preprint 2022 [PDF]
FedEgo: Privacy-preserving Personalized Federated Graph Learning with Ego-graphs SYSU preprint 2022 [PDF] [CODE]
Federated Graph Contrastive Learning UTS preprint 2022 [PDF]
FD-GATDR: A Federated-Decentralized-Learning Graph Attention Network for Doctor Recommendation Using EHR preprint 2022 [PDF]
Privacy-preserving Graph Analytics: Secure Generation and Federated Learning preprint 2022 [PDF]
Federated Graph Attention Network for Rumor Detection preprint 2022 [PDF] [CODE]
FedRel: An Adaptive Federated Relevance Framework for Spatial Temporal Graph Learning preprint 2022 [PDF]
Privatized Graph Federated Learning preprint 2022 [PDF]
Federated Graph Neural Networks: Overview, Techniques and Challenges surv. preprint 2022 [PDF]
Decentralized event-triggered federated learning with heterogeneous communication thresholds. preprint 2022 [PDF]
Federated Learning with Heterogeneous Architectures using Graph HyperNetworks preprint 2022 [PDF]
STFL: A Temporal-Spatial Federated Learning Framework for Graph Neural Networks preprint 2021 [PDF] [CODE]
PPSGCN: A Privacy-Preserving Subgraph Sampling Based Distributed GCN Training Method preprint 2021 [PDF]
Leveraging a Federation of Knowledge Graphs to Improve Faceted Search in Digital Libraries kg. preprint 2021 [PDF]
Federated Myopic Community Detection with One-shot Communication preprint 2021 [PDF]
Federated Graph Learning -- A Position Paper surv. preprint 2021 [PDF]
A Vertical Federated Learning Framework for Graph Convolutional Network preprint 2021 [PDF]
FedGL: Federated Graph Learning Framework with Global Self-Supervision preprint 2021 [PDF]
FL-AGCNS: Federated Learning Framework for Automatic Graph Convolutional Network Search preprint 2021 [PDF]
A New Look and Convergence Rate of Federated Multi-Task Learning with Laplacian Regularization preprint 2021 [PDF] [CODE]
Improving Federated Relational Data Modeling via Basis Alignment and Weight Penalty kg. preprint 2020 [PDF]
GraphFederator: Federated Visual Analysis for Multi-party Graphs preprint 2020 [PDF]
Privacy-Preserving Graph Neural Network for Node Classification preprint 2020 [PDF]
Peer-to-peer federated learning on graphs UC preprint 2019 [PDF] [解读]

Private Graph Neural Networks (todo)

  • [Arxiv 2021] Privacy-Preserving Graph Convolutional Networks for Text Classification. [PDF]
  • [Arxiv 2021] GraphMI: Extracting Private Graph Data from Graph Neural Networks. [PDF]
  • [Arxiv 2021] Towards Representation Identical Privacy-Preserving Graph Neural Network via Split Learning. [PDF]
  • [Arxiv 2020] Locally Private Graph Neural Networks. [PDF]
Private Graph Neural Networks (todo)

fl on tabular data

dblp

This section refers to DBLP search engine.

fl on tabular data
Title Affiliation Venue Year Materials
SGBoost: An Efficient and Privacy-Preserving Vertical Federated Tree Boosting Framework Xidian University IEEE Trans. Inf. Forensics Secur. 🎓 2023 [PUB] [CODE]
Incentive-boosted Federated Crowdsourcing SDU AAAI 🎓 2023 [PDF]
Explaining predictions and attacks in federated learning via random forests Universitat Rovira i Virgili Appl. Intell. 2023 [PUB] [CODE]
Boosting Accuracy of Differentially Private Federated Learning in Industrial IoT With Sparse Responses IEEE Trans. Ind. Informatics 2023 [PUB]
Driver Drowsiness EEG Detection Based on Tree Federated Learning and Interpretable Network. Int. J. Neural Syst. 2023 [PUB]
FDPBoost: Federated differential privacy gradient boosting decision trees. J. Inf. Secur. Appl. 2023 [PUB]
Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates. EuroMLSys 2023 [PUB] [PDF]
HT-Fed-GAN: Federated Generative Model for Decentralized Tabular Data Synthesis HIT Entropy 2023 [PUB]
Blockchain-Based Swarm Learning for the Mitigation of Gradient Leakage in Federated Learning University of Udine IEEE Access 2023 [PUB]
OpBoost: A Vertical Federated Tree Boosting Framework Based on Order-Preserving Desensitization ZJU Proc. VLDB Endow. 🎓 2022 [PUB] [PDF] [CODE]
RevFRF: Enabling Cross-Domain Random Forest Training With Revocable Federated Learning XIDIAN UNIVERSITY IEEE Trans. Dependable Secur. Comput. 🎓 2022 [PUB] [PDF]
A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources University of Pittsburgh ICML 🎓 2022 [PUB] [PDF] [CODE]
Federated Boosted Decision Trees with Differential Privacy University of Warwick CCS 🎓 2022 [PUB] [PDF] [CODE]
Federated Functional Gradient Boosting University of Pennsylvania AISTATS 🎓 2022 [PUB] [PDF] [CODE]
Tree-Based Models for Federated Learning Systems. IBM Research Federated Learning 2022 [PUB]
Federated Learning for Tabular Data using TabNet: A Vehicular Use-Case ICCP 2022 [PUB]
Federated Learning for Tabular Data: Exploring Potential Risk to Privacy Newcastle University ISSRE 2022 [PDF]
Federated Random Forests can improve local performance of predictive models for various healthcare applications University of Marburg Bioinform. 2022 [PUB] [CODE]
FLForest: Byzantine-robust Federated Learning through Isolated Forest NUAA ICPADS 2022 [PUB]
Boosting the Federation: Cross-Silo Federated Learning without Gradient Descent. unito IJCNN 2022 [PUB] [CODE]
Federated Forest JD TBD 2022 [PUB] [PDF]
Sliding Focal Loss for Class Imbalance Classification in Federated XGBoost. Swinburne University of Technology ISPA/BDCloud/SocialCom/SustainCom 2022 [PUB]
Neural gradient boosting in federated learning for hemodynamic instability prediction: towards a distributed and scalable deep learning-based solution. AMIA 2022 [PUB]
Fed-GBM: a cost-effective federated gradient boosting tree for non-intrusive load monitoring The University of Sydney e-Energy 2022 [PUB]
Verifiable Privacy-Preserving Scheme Based on Vertical Federated Random Forest NUST IEEE Internet Things J. 2022 [PUB]
Statistical Detection of Adversarial examples in Blockchain-based Federated Forest In-vehicle Network Intrusion Detection Systems CNU IEEE Access 2022 [PUB] [PDF]
BOFRF: A Novel Boosting-Based Federated Random Forest Algorithm on Horizontally Partitioned Data METU IEEE Access 2022 [PUB]
eFL-Boost: Efficient Federated Learning for Gradient Boosting Decision Trees kobe-u IEEE Access 2022 [PUB]
An Efficient Learning Framework for Federated XGBoost Using Secret Sharing and Distributed Optimization TJU ACM Trans. Intell. Syst. Technol. 2022 [PUB] [PDF] [CODE]
An optional splitting extraction based gain-AUPRC balanced strategy in federated XGBoost for mitigating imbalanced credit card fraud detection Swinburne University of Technology Int. J. Bio Inspired Comput. 2022 [PUB]
Random Forest Based on Federated Learning for Intrusion Detection Malardalen University AIAI 2022 [PUB]
Cross-silo federated learning based decision trees ETH Zürich SAC 2022 [PUB]
Leveraging Spanning Tree to Detect Colluding Attackers in Federated Learning Missouri S&T INFCOM Workshops 2022 [PUB]
VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning PKU SIGMOD 🎓 2021 [PUB]
Boosting with Multiple Sources Google NeurIPS:mortar_board: 2021 [PUB]
SecureBoost: A Lossless Federated Learning Framework 🔥 UC IEEE Intell. Syst. 2021 [PUB] [PDF] [SLIDE] [CODE] [解读] [UC]
A Blockchain-Based Federated Forest for SDN-Enabled In-Vehicle Network Intrusion Detection System CNU IEEE Access 2021 [PUB]
Research on privacy protection of multi source data based on improved gbdt federated ensemble method with different metrics NCUT Phys. Commun. 2021 [PUB]
Fed-EINI: An Efficient and Interpretable Inference Framework for Decision Tree Ensembles in Vertical Federated Learning UCAS; CAS IEEE BigData 2021 [PUB] [PDF]
Gradient Boosting Forest: a Two-Stage Ensemble Method Enabling Federated Learning of GBDTs THU ICONIP 2021 [PUB]
A k-Anonymised Federated Learning Framework with Decision Trees Umeå University DPM/CBT @ESORICS 2021 [PUB]
AF-DNDF: Asynchronous Federated Learning of Deep Neural Decision Forests Chalmers SEAA 2021 [PUB]
Compression Boosts Differentially Private Federated Learning Univ. Grenoble Alpes EuroS&P 2021 [PUB] [PDF]
Practical Federated Gradient Boosting Decision Trees NUS; UWA AAAI 🎓 2020 [PUB] [PDF] [CODE]
Privacy Preserving Vertical Federated Learning for Tree-based Models NUS VLDB 🎓 2020 [PUB] [PDF] [VIDEO] [CODE]
Boosting Privately: Federated Extreme Gradient Boosting for Mobile Crowdsensing Xidian University ICDCS 2020 [PUB] [PDF]
FedCluster: Boosting the Convergence of Federated Learning via Cluster-Cycling University of Utah IEEE BigData 2020 [PUB] [PDF]
New Approaches to Federated XGBoost Learning for Privacy-Preserving Data Analysis kobe-u ICONIP 2020 [PUB]
Bandwidth Slicing to Boost Federated Learning Over Passive Optical Networks Chalmers University of Technology IEEE Communications Letters 2020 [PUB]
DFedForest: Decentralized Federated Forest UFRJ Blockchain 2020 [PUB]
Straggler Remission for Federated Learning via Decentralized Redundant Cayley Tree Stevens Institute of Technology LATINCOM 2020 [PUB]
Federated Soft Gradient Boosting Machine for Streaming Data Sinovation Ventures AI Institute Federated Learning 2020 [PUB] [解读]
Federated Learning of Deep Neural Decision Forests Fraunhofer-Chalmers Centre LOD 2019 [PUB]
Privet: A Privacy-Preserving Vertical Federated Learning Service for Gradient Boosted Decision Tables. preprint 2023 [PDF]
V2X-Boosted Federated Learning for Cooperative Intelligent Transportation Systems with Contextual Client Selection. preprint 2023 [PDF]
GTV: Generating Tabular Data via Vertical Federated Learning preprint 2023 [PDF]
Federated Survival Forests preprint 2023 [PDF]
Fed-TDA: Federated Tabular Data Augmentation on Non-IID Data HIT preprint 2022 [PDF]
Data Leakage in Tabular Federated Learning ETH Zurich preprint 2022 [PDF]
Boost Decentralized Federated Learning in Vehicular Networks by Diversifying Data Sources preprint 2022 [PDF]
Federated XGBoost on Sample-Wise Non-IID Data preprint 2022 [PDF]
Hercules: Boosting the Performance of Privacy-preserving Federated Learning preprint 2022 [PDF]
FedGBF: An efficient vertical federated learning framework via gradient boosting and bagging preprint 2022 [PDF]
A Fair and Efficient Hybrid Federated Learning Framework based on XGBoost for Distributed Power Prediction. THU preprint 2022 [PDF]
An Efficient and Robust System for Vertically Federated Random Forest preprint 2022 [PDF]
Efficient Batch Homomorphic Encryption for Vertically Federated XGBoost. BUAA preprint 2021 [PDF]
Guess what? You can boost Federated Learning for free preprint 2021 [PDF]
SecureBoost+ : A High Performance Gradient Boosting Tree Framework for Large Scale Vertical Federated Learning 🔥 preprint 2021 [PDF] [CODE]
Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data preprint 2021 [PDF]
FedXGBoost: Privacy-Preserving XGBoost for Federated Learning TUM preprint 2021 [PDF]
Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning preprint 2020 [PDF]
FederBoost: Private Federated Learning for GBDT ZJU preprint 2020 [PDF]
Privacy Preserving Text Recognition with Gradient-Boosting for Federated Learning preprint 2020 [PDF] [CODE]
Cloud-based Federated Boosting for Mobile Crowdsensing preprint 2020 [ARXIV]
Federated Extra-Trees with Privacy Preserving preprint 2020 [PDF]
Bandwidth Slicing to Boost Federated Learning in Edge Computing preprint 2019 [PDF]
Revocable Federated Learning: A Benchmark of Federated Forest preprint 2019 [PDF]
The Tradeoff Between Privacy and Accuracy in Anomaly Detection Using Federated XGBoost CUHK preprint 2019 [PDF] [CODE]

framework

federated learning framework

table

Note: SG means Support for Graph data and algorithms, ST means Support for Tabular data and algorithms.

federated learning framework
Platform Papers Affiliations SG ST Materials
PySyft
Stars
 A generic framework for privacy preserving deep learning OpenMined [DOC]
FATE
Stars
 FATE: An Industrial Grade Platform for Collaborative Learning With Data Protection WeBank ✅✅ [DOC] [DOC(ZH)]
Flower
Stars
 Flower: A Friendly Federated Learning Research Framework flower.ai [DOC]
FedML
Stars
 FedML: A Research Library and Benchmark for Federated Machine Learning FedML ✅✅ ✅ [DOC]
TFF(Tensorflow-Federated)
Stars
 Towards Federated Learning at Scale: System Design Google [DOC] [PAGE]
SecretFlow
Stars
 Ant group ✅ [DOC]
PFLlib
Stars
 PFLlib: Personalized Federated Learning Algorithm Library SJTU
Primihub
Stars
 primihub [DOC]
FederatedScope
Stars
 FederatedScope: A Flexible Federated Learning Platform for Heterogeneity Alibaba DAMO Academy ✅✅ [DOC] [PAGE]
Fedlearner
Stars
 Bytedance
LEAF
Stars
 LEAF: A Benchmark for Federated Settings CMU
Fedlab
Stars
 FedLab: A Flexible Federated Learning Framework SMILELab [DOC] [DOC(ZH)] [PAGE]
OpenFL
Stars
 OpenFL: An open-source framework for Federated Learning Intel [DOC]
NVFlare
Stars
 NVIDIA FLARE: Federated Learning from Simulation to Real-World NVIDIA [DOC]
Privacy Meter
Stars
 Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning University of Massachusetts Amherst
Rosetta
Stars
 matrixelements [DOC] [PAGE]
NIID-Bench
Stars
 Federated Learning on Non-IID Data Silos: An Experimental Study Xtra Computing Group
PaddleFL
Stars
 Baidu [DOC]
IBM Federated Learning
Stars
 IBM Federated Learning: an Enterprise Framework White Paper IBM ✅ [PAPERS]
FLGo
Stars
 Federated Learning with Fair Averaging
FLGo: A Fully Customizable Federated Learning Platform		 XMU
KubeFATE
Stars
 WeBank [WIKI]
FedScale
Stars
 FedScale: Benchmarking Model and System Performance of Federated Learning at Scale SymbioticLab(U-M)
Differentially Private Federated Learning: A Client-level Perspective
Stars
 Differentially Private Federated Learning: A Client Level Perspective SAP-samples
PersonalizedFL
Stars
img		 microsoft
plato
Stars
 Plato: An Open-Source Research Framework for Production Federated Learning UofT
Backdoors 101
Stars
 Blind Backdoors in Deep Learning Models Cornell Tech
SWARM LEARNING
Stars
 Swarm Learning for decentralized and confidential clinical machine learning [VIDEO]
EasyFL
Stars
 EasyFL: A Low-code Federated Learning Platform For Dummies NTU
substra
Stars
 Substra [DOC]
FedJAX
Stars
 FEDJAX: Federated learning simulation with JAX Google
Breaching
Stars
 A Framework for Attacks against Privacy in Federated Learning (papers)
FLSim
Stars
 facebook research
Galaxy Federated Learning
Stars
 GFL: A Decentralized Federated Learning Framework Based On Blockchain ZJU [DOC]
FedNLP
Stars
 FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks FedML
PyVertical
Stars
 PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN OpenMined
Xaynet
Stars
 XayNet [PAGE] [DOC] [WHITEPAPER] [LEGAL REVIEW]
SyferText
Stars
 OpenMined
FLSim
Stars
 Optimizing Federated Learning on Non-IID Data with Reinforcement Learning University of Toronto
FLUTE
Stars
 FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations microsoft [DOC]
FedGraphNN
Stars
 FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks FedML ✅✅
FedTorch
Stars
 Distributionally Robust Federated Averaging Penn State
PhotoLabeller
Stars
 [BLOG]
FedTree
Stars
 FedTree: A Federated Learning System For Trees Xtra Computing Group ✅✅ [DOC]
FEDn
Stars
 Scalable federated machine learning with FEDn scaleoutsystems [DOC]
FATE-Serving
Stars
 WeBank [DOC]
PriMIA
Stars
 End-to-end privacy preserving deep learning on multi-institutional medical imaging TUM; Imperial College London; OpenMined [DOC]
9nfl
Stars
 JD
FedLearn
Stars
 Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform JD
FeTS
Stars
 The federated tumor segmentation (FeTS) tool: an open-source solution to further solid tumor research Federated Tumor Segmentation (FeTS) initiative [DOC]
APPFL
Stars
 APPFL: open-source software framework for privacy-preserving federated learning [DOC]
FedCV
Stars
 FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks FedML
MPLC
Stars
 LabeliaLabs [PAGE]
Flame
Stars
 Flame: Simplifying Topology Extension in Federated Learning Cisco [DOC]
FlexCFL
Stars
 Flexible Clustered Federated Learning for Client-Level Data Distribution Shift Chongqing University
FedGroup
Stars
 FedGroup: Efficient Clustered Federated Learning via Decomposed Data-Driven Measure Chongqing University
FedEval
Stars
 FedEval: A Benchmark System with a Comprehensive Evaluation Model for Federated Learning HKU [DOC]
UCADI
Stars
 Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence Huazhong University of Science and Technology
OpenFed
Stars
 OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework [DOC]
FedSim
Stars
GOLF
Stars
 SYSU [DOC]
Federated-Learning-source
Stars
 A Practical Federated Learning Framework for Small Number of Stakeholders ETH Zürich [DOC]
Clara NVIDIA
OpenHealth
Stars
 ZJU

benchmark

  • UniFed leaderboard

Here's a really great Benchmark for the federated learning open source framework 👍 UniFed leaderboard, which present both qualitative and quantitative evaluation results of existing popular open-sourced FL frameworks, from the perspectives of functionality, usability, and system performance.

workflow-design

UniFed_framework_benchmark

For more results, please refer to Framework Functionality Support

datasets

fl graph datasets

tabular datasets

fl datasets

surveys

This section partially refers to repository Federated-Learning and FederatedAI research , the order of the surveys is arranged in reverse order according to the time of first submission (the latest being placed at the top)

  • [Ad Hoc Networks 2024] Privacy Computing Meets Metaverse: Necessity, Taxonomy and Challenges PUB PDF CODE
  • [SIGKDD Explor. 2022] Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications PUB PDF
  • [ACM Trans. Interact. Intell. Syst.] Toward Responsible AI: An Overview of Federated Learning for User-centered Privacy-preserving Computing PUB
  • [ICML Workshop 2020] SECure: A Social and Environmental Certificate for AI Systems PDF
  • [IEEE Commun. Mag. 2020] From Federated Learning to Fog Learning: Towards Large-Scale Distributed Machine Learning in Heterogeneous Wireless Networks PDF [PUB]
  • [China Communications 2020] Federated Learning for 6G Communications: Challenges, Methods, and Future Directions PDF PUB
  • [Federated Learning Systems] A Review of Privacy Preserving Federated Learning for Private IoT Analytics PDF [PUB]
  • [WorldS4 2020] Survey of Personalization Techniques for Federated Learning PDF PUB
  • Towards Utilizing Unlabeled Data in Federated Learning: A Survey and Prospective PDF
  • [IEEE Internet Things J. 2022] A Survey on Federated Learning for Resource-Constrained IoT Devices PDF PUB
  • [IEEE Communications Surveys & Tutorials 2020] Communication-Efficient Edge AI: Algorithms and Systems PDF PUB
  • [IEEE Communications Surveys & Tutorials 2020] Federated Learning in Mobile Edge Networks: A Comprehensive Survey PDF PUB
  • [IEEE Signal Process. Mag. 2020] Federated Learning: Challenges, Methods, and Future Directions PDF [PUB]
  • [IEEE Commun. Mag. 2020] Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges PDF PUB
  • [IEEE TKDE 2021] A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection PDF PUB
  • [IJCAI Workshop 2020] Threats to Federated Learning: A Survey PDF
  • [Foundations and Trends in Machine Learning 2021] Advances and Open Problems in Federated Learning PDF PUB
  • Privacy-Preserving Blockchain Based Federated Learning with Differential Data Sharing PDF
  • An Introduction to Communication Efficient Edge Machine Learning PDF
  • [IEEE Communications Surveys & Tutorials 2020] Convergence of Edge Computing and Deep Learning: A Comprehensive Survey PDF PUB
  • [IEEE TIST 2019] Federated Machine Learning: Concept and Applications PDF [PUB]
  • [J. Heal. Informatics Res. 2021] Federated Learning for Healthcare Informatics PDF PUB
  • Federated Learning for Coalition Operations PDF
  • No Peek: A Survey of private distributed deep learning PDF

tutorials and courses

tutorials

course

secret sharing

key conferences/workshops/journals

This section partially refers to The Federated Learning Portal.

workshops

  • [FL@FM-IJCAI'24], International Workshop on Federated Learning in the Age of Foundation Models In Conjunction with IJCAI 2024, Jeju Island, South Korea
  • [FL@FM-ICME'24],International Workshop on Federated Learning and Foundation Models for Multi-Media, Niagara Falls, ON, Canada
  • [FL@FM-TheWebConf'24], International Workshop on Federated Foundation Models for the Web 2024 , Singapore
  • [FL@FM-Singapore'24], Federated Learning in the Age of Foundation Models, Summer School @ Singapore 2024, Singapore
  • [TTIC Chicago Summer Workshop] New Frontiers in Federated Learning (Recent Theoretical Advances & Practice), TTIC Chicago, USA
  • [Federated and Collaborative Learning] Calvin Lab Auditorium
  • [FL@FM-NeurIPS'23],International Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS 2023(FL@FM-NeurIPS’23), New Orleans, LA, USA
  • [2nd MBZUAI Workshop] 2nd MBZUAI Workshop on Collaborative Learning: Empowering Sustainable Futures, Abu Dhabi, UAE
  • [FL-CVPR'23], 2nd Workshop on Federated Learning for Computer Vision
  • [FL@FM-AJCAI'23], Workshop on Federated Learning in Australasia: When FL meets Foundation Models in Conjunction with AJCAI 2023, Brisbane, Australia
  • [FL-IJCAI'23], International Workshop on Trustworthy Federated Learning in Conjunction with IJCAI 2023 (FL-IJCAI'23), Macau
  • [FL-KDD'23], International Workshop on Federated Learning for Distributed Data Mining Co-located with the 29th ACM SIGKDD Conference (KDD 2023), Long Beach, CA, USA
  • [FL-ICML'23],Federated Learning and Analytics in Practice: Algorithms, Systems, Applications, and Opportunities Workshop at ICML 2023, Honolulu, HI, USA
  • [FLIRT-SIGIR'23],1st Workshop on Federated Learning for Information ReTrieval, Taipei, Taiwan
  • [FLSys'23], the Federated Learning Systems (FLSys) Workshop @ MLSys 2023, Miami, FL, USA
  • [FLW@TheWebConf'23], 1st Workshop on Federated Learning Technologies, Austin, TX, USA
  • [CIKM'22] The 1st International Workshop on Federated Learning with Graph Data (FedGraph), Atlanta, GA, USA
  • [AI Technology School 2022] Trustable, Verifiable and Auditable Artificial Intelligence, Singapore
  • [FL-CVPR'22] First International Workshop on Federated Learning for Computer Vision (FedVision)
  • [FL-NeurIPS'22] International Workshop on Federated Learning: Recent Advances and New Challenges in Conjunction with NeurIPS 2022 , New Orleans, LA, USA
  • [FL-IJCAI'22] International Workshop on Trustworthy Federated Learning in Conjunction with IJCAI 2022, Vienna, Austria
  • [FL-AAAI-22] International Workshop on Trustable, Verifiable and Auditable Federated Learning in Conjunction with AAAI 2022, Vancouver, BC, Canada (Virtual)
  • [FL-MobiCom'22] FedEdge 2022, 1st ACM Workshop on Data Privacy and Federated Learning Technologies for Mobile Edge Network -Research Track, Sydney, Australia
  • [FL-NeurIPS'21] New Frontiers in Federated Learning: Privacy, Fairness, Robustness, Personalization and Data Ownership, (Virtual)
  • [The Federated Learning Workshop, 2021] , Paris, France (Hybrid)
  • [PDFL-EMNLP'21] Workshop on Parallel, Distributed, and Federated Learning, Bilbao, Spain (Virtual)
  • [FTL-IJCAI'21] International Workshop on Federated and Transfer Learning for Data Sparsity and Confidentiality in Conjunction with IJCAI 2021, Montreal, QB, Canada (Virtual)
  • [DeepIPR-IJCAI'21] Toward Intellectual Property Protection on Deep Learning as a Services, Montreal, QB, Canada (Virtual)
  • [FL-ICML'21] International Workshop on Federated Learning for User Privacy and Data Confidentiality, (Virtual)
  • [RSEML-AAAI-21] Towards Robust, Secure and Efficient Machine Learning, (Virtual)
  • [NeurIPS-SpicyFL'20] Workshop on Scalability, Privacy, and Security in Federated Learning, Vancouver, BC, Canada (Virtual)
  • [FL-IJCAI'20] International Workshop on Federated Learning for User Privacy and Data Confidentiality, Yokohama, Japan (Virtual)
  • [FL-ICML'20] International Workshop on Federated Learning for User Privacy and Data Confidentiality, Vienna, Austria (Virtual)
  • [FL-IBM'20] Workshop on Federated Learning and Analytics, New York, NY, USA
  • [FL-NeurIPS'19] Workshop on Federated Learning for Data Privacy and Confidentiality (in Conjunction with NeurIPS 2019), Vancouver, BC, Canada
  • [FL-IJCAI'19] International Workshop on Federated Learning for User Privacy and Data Confidentiality in Conjunction with IJCAI 2019, Macau
  • [FL-Google'19] Workshop on Federated Learning and Analytics, Seattle, WA, USA

journal special issues

conference special tracks

update log

  • 2024/12/10 - add NeurIPS 2024 papers
  • 2024/12/08 - add IJCV, IJCAI, MM, EMNLP, DAC 2024 papers
  • 2024/12/05 - add TPDS, TCAD, ECCV 2024 papers
  • 2024/09/30 - add JMLR, KDD, S&P, NDSS, NAACL, INFOCOM, ISCA, TC, ICML 2024 papers
  • 2024/07/14 - add CVPR, MLSys, MobiCom, SIGIR 2024 papers
  • 2024/05/20 - add WWW 2024 papers
  • 2024/05/12 - add AISTATS, EuroSys 2024 papers
  • 2024/04/15 - add TPAMI, VLDB 2024 papers
  • 2024/04/10 - add WSDM, Mach Learn 2024 papers
  • 2024/03/28 - add AAAI, TC, TPAMI, TPDS, VLDB 2024 papers
  • 2024/03/08 - add TPAMI, TC, TCAD 2024 papers
  • 2024/02/23 - add ICLR 2024 papers
  • 2024/01/02 - add NeurIPS 2023 papers
  • 2023/12/13 - add MM, CCS, EMNLP 2023 papers and update VLDB, TC, TCAD papers
  • 2023/10/07 - add ICCV 2023 papers
  • 2023/09/18 - add INFOCOM, S&P 2023 papers
  • 2023/08/18 - add COLT 2023 paper
  • 2023/08/16 - refresh KDD, IJCAI 2023 papers
  • 2023/08/02 - refresh ICML 2023 information
  • 2023/07/31 - add MobiCom, ICDE, EuroSys, USENIX Security 2023 papers
  • 2023/07/24 - add SIGIR, UAI, ICSE 2023 papers and information on CVPR workshops
  • 2023/07/03 - add Events for different conferences and journals like ACL
  • 2023/07/01 - add AAAI, ICML, IJCAI, SIGIR, KDD, ACL 2023 papers
  • 2023/06/28 - add AISTATS, MLsys, JMLR, Machine Learning, ALT, FOCS, STOC papers
  • 2023/06/06 - remove 'tldr information' and change this repo from "Awesome-Federated-Learning-on-Graph-and-Tabular-Data" into "Awesome-FL". 📈
  • 2023/05/23 - add CVPR 2023 papers
  • 2023/05/07 - add workshops and WWW 2023 papers
  • 2023/04/02 - add NDSS 2023 papers and fix some typos
  • 2023/02/19 - add INFOCOM 2023 papers
  • 2023/02/14 - add EMNLP 2022 papers
  • 2023/02/13 - add ICLR 2023 papers
  • 2023/01/14 - add UAI 2022 papers, refresh system (TCAD +1, TPDS+8), ML (TPAMI +1,UAI +6), network(MobiCom +3) fields papers
  • 2022/11/24 - refresh NeurIPS 2022,2021 and ICLR 2022 papers
  • 2022/11/06- add S&P 2023 papers
  • 2022/10/29 - add WSDM 2023 paper
  • 2022/10/20 - add CCS, MM, ECCV 2022 papers
  • 2022/10/16 - add AI, JMLR, TPAMI, IJCV, TOCS, TOS, TCAD, TC papers
  • 2022/10/13 - add DAC papers
  • 2022/10/09 - add MobiCom 2022 paper
  • 2022/09/19 - add NeurIPS 2022 papers
  • 2022/09/16 - repository is online with Github Pages
  • 2022/09/06 - add information about FL on Tabular and Graph data
  • 2022/09/05 - add some information about top journals and add TPDS papers
  • 2022/08/31 - all papers (including 400+ papers from top conferences and top journals and 100+ papers with graph and tabular data) have been comprehensively sorted out, and information such as publication addresses, links to preprints and source codes of these papers have been compiled. The source code of 280+ papers has been obtained. We hope it can help those who use this project. 😃
  • 2022/07/31 - add VLDB papers
  • 2022/07/30 - add top-tier system conferences papers and add COLT,UAI,OSDI, SOSP, ISCA, MLSys, AISTATS,WSDM papers
  • 2022/07/28 - add a list of top-tier conferences papers and add IJCAI,SIGIR,SIGMOD,ICDE,WWW,SIGCOMM.INFOCOM,WWW papers
  • 2022/07/27 - add some ECCV 2022 papers
  • 2022/07/22 - add CVPR 2022 and MM 2020,2021 papers
  • 2022/07/21 - give TL;DR and interpret information(解读) of papers. And add KDD 2022 papers
  • 2022/07/15 - give a list of papers in the field of federated learning in top NLP/Secure conferences. And add ICML 2022 papers
  • 2022/07/14 - give a list of papers in the field of federated learning in top ML/CV/AI/DM conferences from innovation-cat‘s Awesome-Federated-Machine-Learning and find 🔥 papers(code is available & stars >= 100)
  • 2022/07/12 - added information about the last commit time of the federated learning open source framework (can be used to determine the maintenance of the code base)
  • 2022/07/12 - give a list of papers in the field of federated learning in top journals
  • 2022/05/25 - complete the paper and code lists of FL on tabular data and Tree algorithms
  • 2022/05/25 - add the paper list of FL on tabular data and Tree algorithms
  • 2022/05/24 - complete the paper and code lists of FL on graph data and Graph Neural Networks
  • 2022/05/23 - add the paper list of FL on graph data and Graph Neural Networks
  • 2022/05/21 - update all of Federated Learning Framework

acknowledgments

Many thanks ❤️ to the other awesome list:

citation

@misc{Awesome-FL,
    title = {Awesome-FL},
    author = {Yuwen Yang and Bingjie Yan and Xuefeng Jiang and Hongcheng Li and Jian Wang and Jiao Chen and Xiangmou Qu and Chang Liu and others},
    year = {2022},
    url = {https://github.com/youngfish42/Awesome-FL}
}

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