Lesi Chen (陈乐偲)

Lesi Chen (陈乐偲)

PhD student, IIIS, Tsinghua

Research

I have a broad interest in optimization theory (especially inspired by theoretical computer science). Currently, I am primarily focusing on the complexity of multi-agent optimization (MAOPT). In my representative work ⭐, I have collaborated with my excellent coauthors to solve many fundamental problems in MAOPT, including the complexity of first-order bilevel optimization [2,7], high-order min(-max) optimization [1,3], and decentralized optimization [9].

Selected Publications

1 indicates co-first-authors; # indicates undergraduate students primarily supervised by me.

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

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

  3. Lesi Chen, Chengchang Liu, Luo Luo, and Jingzhao Zhang, Computationally Faster Newton Methods by Lazy Evaluations , arXiv preprint (extended from ICLR 2025 below). [arXiv 2025] ⭐

  4. Lesi Chen1, Chengchang Liu1, and Jingzhao Zhang, Second-Order Min-Max Optimization with Lazy Hessians, in International Conference on Learning Representations. (Oral) top 1.8% [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 (JMLR), 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, Haishan Ye, and Luo Luo, An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization, in International Conference on Artificial Intelligence and Statistics. [AISTATS 2024]

  9. Luo Luo, Yunyan Bai, Lesi Chen, Yuxing Liu, Haishan Ye, On the Complexity of Decentralized Smooth Nonconvex Finite-Sum Optimization , arXiv preprint. [arXiv 2022] ⭐

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

  11. 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.