From 26963a6be84f8b9f055b158411a842e1e04ba472 Mon Sep 17 00:00:00 2001 From: ttt-noora <72697265+ttt-noora@users.noreply.github.com> Date: Tue, 30 Jul 2024 19:37:02 +0800 Subject: [PATCH] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index cfa25b13e..9ed20f721 100644 --- a/README.md +++ b/README.md @@ -262,7 +262,7 @@ For each algorithm family, we try to provide several *representative* applicatio * Natural Evolution Strategies (NES) * Wierstra, D., Schaul, T., Glasmachers, T., Sun, Y., Peters, J. and Schmidhuber, J., 2014. [Natural evolution strategies](https://jmlr.org/papers/v15/wierstra14a.html). JMLR, 15(1), pp.949-980. * Schaul, T., 2011. [Studies in continuous black-box optimization](https://people.idsia.ch/~schaul/publications/thesis.pdf). Doctoral Dissertation, Technische Universität München. - * Yi, S., Wierstra, D., Schaul, T. and Schmidhuber, J., 2009, June. [Stochastic search using the natural gradient](https://dl.acm.org/doi/10.1145/1553374.1553522). In Proceedings of ICML (pp. 1161-1168). + * Yi, S., Wierstra, D., Schaul, T. and Schmidhuber, J., 2009, June. [Stochastic search using the natural gradient](https://dl.acm.org/doi/10.1145/1553374.1553522). ICML (pp. 1161-1168). * Wierstra, D., Schaul, T., Peters, J. and Schmidhuber, J., 2008, June. [Natural evolution strategies](https://ieeexplore.ieee.org/abstract/document/4631255). CEC (pp. 3381-3387). IEEE. * Applications: e.g., [Yu et al., USENIX Security](https://www.usenix.org/conference/usenixsecurity23/presentation/yuzhiyuan); [Flageat et al., 2023](https://arxiv.org/abs/2303.06137); [Yan et al., 2023](https://arxiv.org/abs/2302.04477); [Feng et al., 2023](https://arxiv.org/abs/2303.06280); [Wei et al., 2022, IJCV](https://link.springer.com/article/10.1007/s11263-022-01604-w); [Agarwal et al., 2022, ICRA](https://ieeexplore.ieee.org/abstract/document/9811565); [Farid et al., 2022, CoRL](https://proceedings.mlr.press/v164/farid22a.html); [Feng et al., 2022, CVPR](https://openaccess.thecvf.com/content/CVPR2022/html/Feng_Boosting_Black-Box_Attack_With_Partially_Transferred_Conditional_Adversarial_Distribution_CVPR_2022_paper.html); [Berliner et al., 2022, ICLR](https://openreview.net/forum?id=JJCjv4dAbyL); [Kirsch et al., 2022, AAAI](https://ojs.aaai.org/index.php/AAAI/article/view/20681); [Jain et al., 2022, USENIX Security](https://www.usenix.org/conference/usenixsecurity22/presentation/jain); [Ilyas et al., 2018, ICML](https://proceedings.mlr.press/v80/ilyas18a.html). * Estimation of Distribution Algorithm (EDA) [ [MIMIC [NeurIPS-1996]](https://proceedings.neurips.cc/paper/1996/hash/4c22bd444899d3b6047a10b20a2f26db-Abstract.html) + [BOA [GECCO-1999]](https://dl.acm.org/doi/abs/10.5555/2933923.2933973) + [[ECJ-2005]](https://direct.mit.edu/evco/article-abstract/13/1/99/1198/Drift-and-Scaling-in-Estimation-of-Distribution) ] @@ -282,7 +282,7 @@ For each algorithm family, we try to provide several *representative* applicatio * Hu, J., Fu, M.C. and Marcus, S.I., 2007. [A model reference adaptive search method for global optimization](https://pubsonline.informs.org/doi/abs/10.1287/opre.1060.0367). Operations Research, 55(3), pp.549-568. * De Boer, P.T., Kroese, D.P., Mannor, S. and Rubinstein, R.Y., 2005. [A tutorial on the cross-entropy method](https://link.springer.com/article/10.1007/s10479-005-5724-z). Annals of Operations Research, 134(1), pp.19-67. * Rubinstein, R.Y. and Kroese, D.P., 2004. [The cross-entropy method: A unified approach to combinatorial optimization, Monte-Carlo simulation, and machine learning](https://link.springer.com/book/10.1007/978-1-4757-4321-0). New York: Springer. - * Mannor, S., Rubinstein, R.Y. and Gat, Y., 2003. [The cross entropy method for fast policy search](https://dl.acm.org/doi/abs/10.5555/3041838.3041903). In Proceedings of ICML (pp. 512-519). + * Mannor, S., Rubinstein, R.Y. and Gat, Y., 2003. [The cross entropy method for fast policy search](https://dl.acm.org/doi/abs/10.5555/3041838.3041903). ICML (pp. 512-519). * Applications: e.g., [Wang&Ba,2020, ICLR](https://openreview.net/forum?id=H1exf64KwH); [Hafner et al., 2019, ICML](https://proceedings.mlr.press/v97/hafner19a.html); [Pourchot&Sigaud, 2019, ICLR](https://openreview.net/forum?id=BkeU5j0ctQ); [Simmons-Edler et al., 2019, ICML-RL4RealLife](https://openreview.net/forum?id=SyeHbtgSiN); [Chua et al., 2018, NeurIPS](https://proceedings.neurips.cc/paper/2018/file/3de568f8597b94bda53149c7d7f5958c-Paper.pdf); [Duan et al., 2016, ICML](https://proceedings.mlr.press/v48/duan16.html); [Kobilarov, 2012, IJRR](https://journals.sagepub.com/doi/10.1177/0278364912444543). * Differential Evolution (DE) * Price, K.V., 2013. [Differential evolution](https://link.springer.com/chapter/10.1007/978-3-642-30504-7_8). In Handbook of Optimization (pp. 187-214). Springer, Berlin, Heidelberg.