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Recent Papers

Multi-view clustering

  1. Wang, Siwei & Liu, Xinwang & Liu, Suyuan & Jin, Jiaqi & Wenxuan, Tu & Zhu, Xinzhong & Zhu, En. (2022). Align then Fusion: Generalized Large-scale Multi-view Clustering with Anchor Matching Correspondences.
  2. Xu, J., Tang, H., Ren, Y., Peng, L., Zhu, X., & He, L. (2022). Multi-Level Feature Learning for Contrastive Multi-View Clustering. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 16051-16060).
  3. Yang, H., Gao, Q., Xia, W., Yang, M., & Gao, X. (2022). Multi-view Spectral Clustering with Bipartite Graph. IEEE Transactions on Image Processing.
  4. Xia, W., Gao, Q., Wang, Q., Gao, X., Ding, C., & Tao, D. (2022). Tensorized Bipartite Graph Learning for Multi-View Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence.
  5. Zhu, Y., Wang, X., Chen, L., & Nie, R. (2022). CEFusion: Multi‐Modal medical image fusion via cross encoder. IET Image Processing.
  6. Liu, J., Liu, J., Yan, S., Jiang, R., Tian, X., Gu, B., ... & Huang, J. (2022). MPC: Multi-View Probabilistic Clustering. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 9509-9518).
  7. Yu, X., Liu, H., Lin, Y., Liu, N., & Sun, S. Sample-Level Weights Learning for Multi-View Clustering on Spectral Rotation. Available at SSRN 4157771.
  8. Li, H., Ren, Z., Zhao, C., Xu, Z., & Dai, J. (2022). Self-paced latent embedding space learning for multi-view clustering. International Journal of Machine Learning and Cybernetics, 1-14.
  9. Zhao, J., Kang, F., Zou, Q., & Wang, X. Multi-View Clustering with Orthogonal Mapping and Binary Graph. Available at SSRN 4137566.
  10. Liu, W., Liu, L., Zhang, Y., Wang, H., & Feng, L. (2022). Adaptive multi-view multiple-means clustering via subspace reconstruction. Engineering Applications of Artificial Intelligence, 114, 104986.
  11. Luong, K., Nayak, R., Balasubramaniam, T., & Bashar, M. A. (2022). Multi-layer Manifold Learning for Deep Non-negative Matrix Factorization-Based Multi-View Clustering. Pattern Recognition, 108815.
  12. Mi, Y., Dai, J., Ren, Z., You, X., & Wang, Y. (2022). One-Stage Multi-view Clustering with Hierarchical Attributes Extraction. Cognitive Computation, 1-13.
  13. Wang, S., Liu, X., Liu, S., Jin, J., Tu, W., Zhu, X., & Zhu, E. (2022). Align then Fusion: Generalized Large-scale Multi-view Clustering with Anchor Matching Correspondences. arXiv preprint arXiv:2205.15075.
  14. Chen, R., Tang, Y., Zhang, W., & Feng, W. (2022). Deep Multi-view Semi-supervised Clustering with Sample Pairwise Constraints. Neurocomputing.
  15. Ma, X., Xue, S., Wu, J., Yang, J., Paris, C., Nepal, S., & Sheng, Q. Z. (2022). Deep Multi-Attributed-View Graph Representation Learning. IEEE Transactions on Network Science and Engineering.
  16. Choudhury, S. J., & Pal, N. R. (2022). Fuzzy Clustering of single-view incomplete data using a multi-view framework. IEEE Transactions on Fuzzy Systems.
  17. Huusari, R., Capponi, C., Villoutreix, P., & Kadri, H. (2022). Cross-View kernel transfer. Pattern Recognition, 129, 108759.
  18. Qin, Y., Feng, G., Ren, Y., & Zhang, X. (2022). Consistency-Induced Multiview Subspace Clustering. IEEE Transactions on Cybernetics.
  19. Gu, Z., & Feng, S. (2022). Individuality Meets Commonality: A Unified Graph Learning Framework for Multi-view Clustering. ACM Transactions on Knowledge Discovery from Data (TKDD)
  20. Zhang, K., Song, J., Yu, Y., & Du, S. (2022, April). Incomplete Multi-View Clustering Based on Weighted Adaptive Graph Learning. In 2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP) (pp. 1175-1179). IEEE.
  21. Yao, L., & Lu, G. F. (2022). Double structure scaled simplex representation for multi-view subspace clustering. Neural Networks, 151, 168-177.
  22. Wang, D., Li, T., Deng, P., Liu, J., Huang, W., & Zhang, F. (2022). A Generalized Deep Learning Algorithm based on NMF for Multi-view Clustering. IEEE Transactions on Big Data.
  23. Wang, B., Wang, Y., He, X., Hu, Y., & Yin, B. (2022). Multi‐graph convolutional clustering network. IET Signal Processing.
  24. Xu, H., Gong, L., Xuan, H., Zheng, X., Gao, Z., & Wen, X. (2022). Multiview clustering via consistent and specific nonnegative matrix factorization with graph regularization. Multimedia Systems, 1-14.
  25. Zhao, L., Zhang, J., Yang, T., & Chen, Z. (2022). Incomplete multi-view clustering based on weighted sparse and low rank representation. Applied Intelligence, 1-17.
  26. Honghan, Z., Weiling, C., Le, X., & Ming, Y. (2021, November). Multi-view Latent Subspace Clustering based on both Global and Local Structure. In Asian Conference on Machine Learning (pp. 1617-1632). PMLR.
  27. Yang, J., & Lin, C. T. (2022). Multi-View Adjacency-Constrained Nearest Neighbor Clustering (Student Abstract). AAAI.
  28. Zhang, J., Li, L., Wang, S., Liu, J., Liu, Y., Liu, X., & Zhu, E. (2022). Multiple Kernel Clustering with Dual Noise Minimization. arXiv preprint arXiv:2207.06041.
  29. Zhang, X., Yang, Y., Zhai, D., Li, T., Chu, J., & Wang, H. (2021). Local2Global: Unsupervised multi-view deep graph representation learning with Nearest Neighbor Constraint. Knowledge-Based Systems, 231, 107439.
  30. Ma, J., Wang, R., Ji, W., Zhao, J., Zong, M., & Gilman, A. (2021). Robust multi-view continuous subspace clustering. Pattern Recognition Letters, 150, 306-312.
  31. Huang, Z., Ren, Y., Pu, X., & He, L. (2021, October). Non-Linear Fusion for Self-Paced Multi-View Clustering. In Proceedings of the 29th ACM International Conference on Multimedia (pp. 3211-3219).
  32. Cai, X., Huang, D., Zhang, G. Y., & Wang, C. D. (2022). Seeking Commonness and Inconsistencies: A Jointly Smoothed Approach to Multi-view Subspace Clustering. arXiv preprint arXiv:2203.08060.
  33. Lin, F., Bai, B., Bai, K., Ren, Y., Zhao, P., & Xu, Z. (2022). Contrastive Multi-view Hyperbolic Hierarchical Clustering. arXiv preprint arXiv:2205.02618.
  34. Liu, J., Liu, J., Yan, S., Jiang, R., Tian, X., Gu, B., ... & Huang, J. (2022). MPC: Multi-View Probabilistic Clustering. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 9509-9518).
  35. Xin, B., Zeng, S., & Wang, X. (2021, July). Self-Supervised Deep Correlational Multi-View Clustering. In 2021 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE. code
  36. Wang, S., Li, C., Li, Y., Yuan, Y., & Wang, G. (2022). Self-Supervised Information Bottleneck for Deep Multi-View Subspace Clustering. arXiv preprint arXiv:2204.12496.
  37. Tsai, Y. H. H., Wu, Y., Salakhutdinov, R., & Morency, L. P. (2020). Self-supervised learning from a multi-view perspective. arXiv preprint arXiv:2006.05576.
  38. Mao, Y., Yan, X., Guo, Q., & Ye, Y. (2021, May). Deep mutual information maximin for cross-modal clustering. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, No. 10, pp. 8893-8901).
  39. Sang, X., Lu, J., & Lu, H. (2022). Consensus Graph Learning for Auto-weighted Multi-view Projection Clustering. Information Sciences.
  40. Liu, L., Chen, P., Luo, G., Kang, Z., Luo, Y., & Han, S. (2022). Scalable multi-view clustering with graph filtering. Neural Computing and Applications, 1-9.
  41. Wan, Zhibin, et al. "Cross-view equivariant auto-encoder." 2021 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 2021.
  42. Yang, M. S., & Sinaga, K. P. (2021). Collaborative feature-weighted multi-view fuzzy c-means clustering. Pattern Recognition, 119, 108064.
  43. Xia, W., Wang, S., Yang, M., Gao, Q., Han, J., & Gao, X. (2022). Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation. Neural Networks, 145, 1-9.
  44. Mi, Y., Dai, J., Ren, Z., You, X., & Wang, Y. (2022). One-Stage Multi-view Clustering with Hierarchical Attributes Extraction. Cognitive Computation, 1-13.
  45. Xu, K., Tang, K., & Su, Z. (2022). Deep multi-view subspace clustering via structure-preserved multi-scale features fusion. Neural Computing and Applications, 1-17.
  46. Zhang, W., Deng, Z., Choi, K. S., Wang, J., & Wang, S. (2022). Dual Representation Learning for One-Step Clustering of Multi-View Data. arXiv preprint arXiv:2208.14450.
  47. Zhao, X., Yan, W., Ren, J., Xu, J., Liu, Z., Yue, G., & Tang, C. (2022). Graph-Filtering and High-Order Bipartite Graph based Multiview Graph Clustering. Digital Signal Processing, 103847.
  48. Yang, H., Liu, Q., Zhang, J., Ding, X., Chen, C., & Wang, L. (2022). Community Detection in Semantic Networks: A Multi-View Approach. Entropy, 24(8), 1141.
  49. Liu, M., Yang, Z., Li, L., Li, Z., & Xie, S. (2022). Auto-weighted collective matrix factorization with graph dual regularization for multi-view clustering. Knowledge-Based Systems, 110145.
  50. Tang, H., & Liu, Y. (2022, June). Deep safe incomplete multi-view clustering: Theorem and algorithm. In International Conference on Machine Learning (pp. 21090-21110). PMLR.
  51. Zhang, X., Ren, Z., & Yang, C. (2022). Center consistency guided multi-view embedding anchor learning for large-scale graph clustering. Knowledge-Based Systems, 110162.
  52. Du, Y., Lu, G. F., & Ji, G. A Multi-View Clustering Method Based on High-Level Information Fusion. Available at SSRN 4278360.
  53. Ou, Q., Wang, S., Zhou, S., Li, M., Guo, X., & Zhu, E. (2020). Anchor-based multiview subspace clustering with diversity regularization. IEEE MultiMedia, 27(4), 91-101.

Incomplete Multi-view clustering

  1. Wen, J., Zhang, Z., Zhang, Z., Fei, L., & Wang, M. (2020). Generalized incomplete multiview clustering with flexible locality structure diffusion. IEEE transactions on cybernetics, 51(1), 101-114.

  2. Zhao, L., Zhang, J., Wang, Q., & Chen, Z. (2021). Dual Alignment Self-Supervised Incomplete Multi-View Subspace Clustering Network. IEEE Signal Processing Letters, 28, 2122-2126.

  3. Wen, J., Zhang, Z., Zhang, Z., Zhu, L., Fei, L., Zhang, B., & Xu, Y. (2021, May). Unified tensor framework for incomplete multi-view clustering and missing-view inferring. In Proceedings of the AAAI conference on artificial intelligence (Vol. 35, No. 11, pp. 10273-10281).

  4. Liu, J., Liu, X., Zhang, Y., Zhang, P., Tu, W., Wang, S., ... & Yang, Y. (2021, October). Self-representation subspace clustering for incomplete multi-view data. In Proceedings of the 29th ACM International Conference on Multimedia (pp. 2726-2734).

  5. Xue, Z., Du, J., Zheng, C., Song, J., Ren, W., & Liang, M. (2021). Clustering-Induced Adaptive Structure Enhancing Network for Incomplete Multi-View Data. In IJCAI (pp. 3235-3241).

  6. Liang, J., Liu, X., Bai, L., Cao, F., & Wang, D. (2022). Incomplete multi-view clustering via local and global co-regularization. Science China Information Sciences, 65(5), 1-16.

  7. Yu, Z., Ye, M., Xiao, S., & Tian, L. (2022). Learning missing instances in latent space for incomplete multi-view clustering. Knowledge-Based Systems, 109122.

  8. Liang, N., Yang, Z., & Xie, S. (2022). Incomplete Multi-view Clustering with Sample-level Auto-weighted Graph Fusion. IEEE Transactions on Knowledge and Data Engineering.

  9. Lv, Z., Gao, Q., Zhang, X., Li, Q., & Yang, M. (2022). View-Consistency Learning for Incomplete Multi-View Clustering. IEEE Transactions on Image Processing.

  10. Liang, N., Yang, Z., Li, Z., & Han, W. (2022). Incomplete multi-view clustering with incomplete graph-regularized orthogonal non-negative matrix factorization. Applied Intelligence, 1-17.

  11. Yu, X., Liu, H., Lin, Y., Wu, Y., & Zhang, C. (2022). Auto-weighted sample-level fusion with anchors for incomplete multi-view clustering. Pattern Recognition, 130, 108772.

  12. Luo, M., Wang, S., Wang, C., Chen, W., Zhu, E., & Liu, X. (2022). DICDP: Deep Incomplete Clustering with Distribution Preserving. In International Conference on Artificial Intelligence and Security (pp. 162-175). Springer, Cham.

  13. Wang, S., Cao, J., Lei, F., Jiang, J., Dai, Q., & Ling, B. W. K. (2022). Multiple kernel-based anchor graph coupled low-rank tensor learning for incomplete multi-view clustering. Applied Intelligence, 1-26.

  14. Lian, Z., Chen, L., Sun, L., Liu, B., & Tao, J. (2022). GCNet: Graph Completion Network for Incomplete Multimodal Learning in Conversation. arXiv preprint arXiv:2203.02177.

  15. Li, Z., Tang, C., Zheng, X., Liu, X., Zhang, W., & Zhu, E. (2022). High-order correlation preserved incomplete multi-view subspace clustering. IEEE Transactions on Image Processing, 31, 2067-2080.

  16. Chen, M. S., Wang, C. D., & Lai, J. H. (2022). Low-rank Tensor Based Proximity Learning for Multi-view Clustering. IEEE Transactions on Knowledge and Data Engineering.

  17. Dong, W., Wu, X. J., & Xu, T. (2022). Multi-view Subspace Clustering via Joint Latent Representations. Neural Processing Letters, 54(3), 1879-1901.

  18. Xia, W., Gao, Q., Wang, Q., & Gao, X. (2022). Tensor completion-based incomplete multiview clustering. IEEE Transactions on Cybernetics.

  19. Liang, N., Yang, Z., Li, L., Li, Z., & Xie, S. (2021). Incomplete Multi-view Clustering with Cross-view Feature Transformation. IEEE Transactions on Artificial Intelligence.

  20. Zhao, S., Fei, L., Wen, J., Wu, J., & Zhang, B. (2021). Intrinsic and Complete Structure Learning Based Incomplete Multiview Clustering. IEEE Transactions on Multimedia.

  21. Wang, S., Liu, X., Li, M., Xu, H., Zhu, X., Gao, F., & Zhu, E. Late Fusion Multi-view Clustering via Global and Local Alignment Maximization.

  22. Wang, Y., Chang, D., Fu, Z., & Zhao, Y. (2021). Incomplete Multi-view Clustering via Cross-view Relation Transfer. arXiv preprint arXiv:2112.00739.

  23. Han, X., Ren, Z., Zou, C., & You, X. (2022). Incomplete multi-view subspace clustering based on missing-sample recovering and structural information learning. Expert Systems with Applications, 118165.

  25. Wang, S., Liu, X., Liu, L., Tu, W., Zhu, X., Liu, J., ... & Zhu, E. (2022). Highly-efficient incomplete large-scale multi-view clustering with consensus bipartite graph. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 9776-9785).

  26. Lin, Y., Gou, Y., Liu, X., Bai, J., Lv, J., & Peng, X. (2022). Dual contrastive prediction for incomplete multi-view representation learning. IEEE Transactions on Pattern Analysis and Machine Intelligence.code

  27. Xu, J., Li, C., Ren, Y., Peng, L., Mo, Y., Shi, X., & Zhu, X. (2022). Deep Incomplete Multi-view Clustering via Mining Cluster Complementarity.

  28. Li, X., Sun, Q., Ren, Z., & Sun, Y. (2022, October). Dynamic Incomplete Multi-view Imputing and Clustering. In Proceedings of the 30th ACM International Conference on Multimedia (pp. 3412-3420).

  29. [Tang, H., & Liu, Y. (2022, June). Deep safe incomplete multi-view clustering: Theorem and algorithm. In International Conference on Machine Learning (pp. 21090-21110). PMLR.] (https://proceedings.mlr.press/v162/tang22c/tang22c.pdf)

  30. Wang, Y., Chang, D., Fu, Z., Wen, J., & Zhao, Y. (2022). Graph Contrastive Partial Multi-View Clustering. IEEE Transactions on Multimedia.

  31. Lin, Y., Gou, Y., Liu, X., Bai, J., Lv, J., & Peng, X. (2022). Dual contrastive prediction for incomplete multi-view representation learning. IEEE Transactions on Pattern Analysis and Machine Intelligence.

  32. Yang, M., Li, Y., Hu, P., Bai, J., Lv, J., & Peng, X. (2022). Robust multi-view clustering with incomplete information. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(1), 1055-1069. code

  33. Liang, T., Meng, M., Lan, M., Yu, J., & Wu, J. (2022, July). Group Correspondence: A Statistical Perspective for Incomplete Multi-View Clustering Augmentation. In 2022 IEEE International Conference on Multimedia and Expo (ICME) (pp. 1-6). IEEE.

  34. Xue, Z., Du, J., Zhu, H., Guan, Z., Long, Y., Zang, Y., & Liang, M. (2022, October). Robust Diversified Graph Contrastive Network for Incomplete Multi-view Clustering. In Proceedings of the 30th ACM International Conference on Multimedia (pp. 3936-3944).

  35. Wang, Q., Ding, Z., Tao, Z., Gao, Q., & Fu, Y. (2021). Generative partial multi-view clustering with adaptive fusion and cycle consistency. IEEE Transactions on Image Processing, 30, 1771-1783.

  36. Xu, J., Li, C., Peng, L., Ren, Y., Shi, X., Shen, H. T., & Zhu, X. (2023). Adaptive Feature Projection with Distribution Alignment for Deep Incomplete Multi-view Clustering. IEEE Transactions on Image Processing. code

  37. Zhang, C., Li, H., Chen, C., Jia, X., & Chen, C. (2022). Low-Rank Tensor Regularized Views Recovery for Incomplete Multiview Clustering. IEEE Transactions on Neural Networks and Learning Systems. code

  38. Liu, C., Wu, Z., Wen, J., Xu, Y., & Huang, C. (2022). Localized sparse incomplete multi-view clustering. IEEE Transactions on Multimedia. code