Featured Publications

Optimization Theory

1. Second-Order Minimax Optimization [Slides in SIAM OP 26]
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   Upper Bound: [COLT 2025] [arXiv 2026]
   Lower Bound: [arXiv 2026]
2. Bilevel Optimization [Slides in SIAM OP 26]
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   Upper Bound: [JMLR 2025]
   Lower Bound: [arXiv 2025]

AI for Optimization

1. Xinliang Zhang ¹, Lesi Chen ¹, Zonghan Li, Jingzhao Zhang, Near-Optimal Second-Order Convex Finite-Sum Optimization under Individual Smoothness, arXiv preprint. [arXiv 2026]

2. Qihao Zhou ¹, Lesi Chen ¹, Luo Luo, Chengchang Liu, Envelope Cubic Regularized Newton Method for Nonconvex-Strongly-Concave Minimax Optimization, arXiv preprint. [arXiv 2026]

3. Xinliang Zhang ¹, Lesi Chen¹, Chengchang Liu, Jingzhao Zhang, Near-Optimal Convex Optimization with Lazy Second-Order Oracles, arXiv preprint. [arXiv 2026]

4. Xinliang Zhang ¹, Lesi Chen¹, Linxuan Pan¹, Chengchang Liu, Junchi Yang, Jingzhao Zhang, Optimal High-Order Methods for Solving Monotone Variational Inequalities, arXiv preprint. [arXiv 2026]

1. Lesi Chen¹, Xinliang Zhang ¹, Junru Li, Chengchang Liu, Luo Luo, and Jingzhao Zhang, Solving Convex-Concave Problems with $\tilde{\mathcal{O}}(\epsilon^{-4/(3p+1)})$ pth-Order Oracle Complexity, arXiv preprint. [arXiv 2026]
   [Extension of COLT 2025 below]

2. Lesi Chen, Chengchang Liu, Luo Luo, John C.S. Lui, and Jingzhao Zhang, Optimal Convex Optimization with Inexact Second-Order Oracles, arXiv preprint. [arXiv 2026]

3. Lesi Chen¹, Kaiyi Ji ¹, and Jingzhao Zhang, On the Condition Number Dependency in Bilevel Optimization, arXiv preprint. [arXiv 2026] ⭐

4. Lesi Chen, Chengchang Liu, Luo Luo, and Jingzhao Zhang, Faster Newton Methods for Convex and Nonconvex Optimization in Gradient Complexity, in Conference on Learning Theory. [COLT 2026]

5. Lesi Chen, Junru Li, El Mahdi Chayti and Jingzhao Zhang, Faster Gradient Methods for Highly-Smooth Stochastic Bilevel Optimization, in International Conference on Learning Representations. [ICLR 2026]

6. Lesi Chen¹, Yaohua Ma¹, and Jingzhao Zhang, Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles, Journal of Machine Learning Research, 1-56. [JMLR 2025] ⭐
   

7. Lesi Chen, Chengchang Liu, Luo Luo, and Jingzhao Zhang, Solving Convex-Concave Problems with $\tilde{\mathcal{O}}(\epsilon^{-4/7})$ pth-Order Oracle Complexity, in Conference on Learning Theory. (Best Student Paper) [COLT 2025] [Extension available above] ⭐

8. Lesi Chen¹, Chengchang Liu¹, and Jingzhao Zhang, Second-Order Min-Max Optimization with Lazy Hessians, in International Conference on Learning Representations. (Oral, <2%) [ICLR 2025]

9. Lesi Chen and Luo Luo, Near-Optimal Algorithms for Making the Gradient Small in Stochastic Minimax Optimization, Journal of Machine Learning Research, 1-44. [JMLR 2024]

10. Huaqing Zhang¹, Lesi Chen¹, Jing Xu, and Jingzhao Zhang, Functionally Constrained Algorithm Solves Convex Simple Bilevel Problems, in Conference on Neural Information Processing Systems.
    [NeurIPS 2024]

11. Lesi Chen¹, Jing Xu¹, and Jingzhao Zhang, On Finding Small Hyper-Gradients in Bilevel Optimization: Hardness Results and Improved Analysis, in Conference on Learning Theory. [COLT 2024]

12. Lesi Chen, Jing Xu, and Luo Luo, Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization, in International Conference on Machine Learning. [ICML 2023]

13. Lesi Chen, Boyuan Yao, and Luo Luo, Faster Stochastic Algorithms for Minimax Optimization under Polyak-Łojasiewicz Condition, in Conference on Neural Information Processing Systems. [NeurIPS 2022]

See Google Scholar for a complete list.