Lesi Chen (陈乐偲)

Lesi Chen (陈乐偲)

PhD student, IIIS, Tsinghua

Research

I have broad interests in modern optimization theory, with a particular focus on game-structure optimization. In my representative work ⭐, I have collaborated with my excellent coauthors to solve many fundamental problems in this area, such as the oracle complexity of convex, nonconvex, minimax, and bilevel optimization.

Research Highlights

Provides (near-)optimal algorithms and matching lower bounds on target precision $\epsilon$.
  1. Second-Order Minimax Optimization [Slides in SIAM OP 26] [Expand]
    Upper Bound: [COLT 2025] [arXiv 2026]
    Lower Bound: [arXiv 2026]
    Second-Order Minimax Optimization Detail
  2. Bilevel Optimization [Slides in SIAM OP 26] [Expand]
    Upper Bound: [JMLR 2025]
    Lower Bound: [arXiv 2025]
    Bilevel Optimization Detail

Working Papers

  1. 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]

  2. 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]
    Preliminary version in Conference on Learning Theory. (Best Student Paper, 2/556) [COLT 2025] ⭐

  3. Lesi Chen1 , Kaiyi Ji 1, and Jingzhao Zhang, On the Condition Number Dependency in Bilevel Optimization, arXiv preprint. [arXiv 2025] ⭐

  4. 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]

Featured Publications

  1. 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] ⭐

  2. 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]

  3. 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] ⭐

  4. 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]

  5. 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]

  6. 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]

  7. 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]

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

  9. 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.