Faster Stochastic Algorithms for Minimax Optimization under Polyak-{\L}ojasiewicz Condition L Chen, B Yao, L Luo Advances in Neural Information Processing Systems (NeurIPS), 2022 | 12 | 2022 |
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization L Chen, J Xu, L Luo International Conference on Machine Learning (ICML), 2023 | 11 | 2023 |
Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles L Chen, Y Ma, J Zhang arXiv preprint arXiv:2306.14853, 2023 | 10* | 2023 |
Near-Optimal Algorithms for Making the Gradient Small in Stochastic Minimax Optimization L Chen, L Luo arXiv preprint arXiv:2208.05925, 2022 | 8 | 2022 |
On Finding Small Hyper-Gradients in Bilevel Optimization: Hardness Results and Improved Analysis L Chen, J Xu, J Zhang Conference on Learning Theory (COLT), 2024 | 6* | 2024 |
An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization L Chen, H Ye, L Luo International Conference on Artificial Intelligence and Statistics (AISTATS), 2024 | 4 | 2024 |
Communication Efficient Distributed Newton Method with Fast Convergence Rates C Liu, L Chen, L Luo, J Lui Conference on Knowledge Discovery and Data Mining (KDD), 2023 | 4 | 2023 |
Functionally Constrained Algorithm Solves Convex Simple Bilevel Problems H Zhang, L Chen, J Xu, J Zhang arXiv preprint arXiv:2409.06530, 2024 | | 2024 |
Decentralized Convex Finite-Sum Optimization with Better Dependence on Condition Numbers Y Liu, L Chen, L Luo International Conference on Machine Learning (ICML), 2024 | | 2024 |