Toward Understanding the Importance of Noise in Training Neural Networks. - Mo Zhou; Tianyi Liu; Yan Li 074; Dachao Lin; Enlu Zhou; Tuo Zhao (ICML, 2019)

Inductive Bias of Gradient Descent based Adversarial Training on Separable Data. - Yan Li 074; Ethan X. Fang; Huan Xu; Tuo Zhao (CoRR, 2019)

Towards Understanding the Importance of Noise in Training Neural Networks. - Mo Zhou; Tianyi Liu; Yan Li 074; Dachao Lin; Enlu Zhou; Tuo Zhao (CoRR, 2019)

Implicit Bias of Gradient Descent based Adversarial Training on Separable Data. - Yan Li 074; Ethan X. Fang; Huan Xu; Tuo Zhao (ICLR, 2020)

Deep Reinforcement Learning with Robust and Smooth Policy. - Qianli Shen; Yan Li 074; Haoming Jiang; Zhaoran Wang 001; Tuo Zhao (ICML, 2020)

Deep Reinforcement Learning with Smooth Policy. - Qianli Shen; Yan Li 074; Haoming Jiang; Zhaoran Wang 001; Tuo Zhao (CoRR, 2020)

Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers. - David Joseph Munzer; Siawpeng Er; Minshuo Chen; Yan Li 074; Naga Sasikanth Mannem; Tuo Zhao; Hua Wang 006 (CoRR, 2020)

Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization. - Tianyi Liu; Yan Li 074; Song Wei; Enlu Zhou; Tuo Zhao (AISTATS, 2021)

Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL. - Minshuo Chen; Yan Li 074; Ethan Wang; Zhuoran Yang; Zhaoran Wang 001; Tuo Zhao (NeurIPS, 2021)

Permutation Invariant Policy Optimization for Mean-Field Multi-Agent Reinforcement Learning: A Principled Approach. - Yan Li 074; Lingxiao Wang 003; Jiachen Yang; Ethan Wang; Zhaoran Wang 001; Tuo Zhao; Hongyuan Zha (CoRR, 2021)

Implicit Regularization of Bregman Proximal Point Algorithm and Mirror Descent on Separable Data. - Yan Li 074; Caleb Ju; Ethan X. Fang; Tuo Zhao (CoRR, 2021)

Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably. - Tianyi Liu; Yan Li 074; Enlu Zhou; Tuo Zhao (AISTATS, 2022)

Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. - Yan Li 074; Dhruv Choudhary; Xiaohan Wei; Baichuan Yuan; Bhargav Bhushanam; Tuo Zhao; Guanghui Lan (ICLR, 2022)

Deep Learning Assisted End-to-End Synthesis of mm-Wave Passive Networks with 3D EM Structures: A Study on A Transformer-Based Matching Network. - Siawpeng Er; Edward Liu; Minshuo Chen; Yan Li 074; Yuqi Liu; Tuo Zhao; Hua Wang 006 (CoRR, 2022)

Homotopic Policy Mirror Descent: Policy Convergence, Implicit Regularization, and Improved Sample Complexity. - Yan Li 074; Tuo Zhao; Guanghui Lan (CoRR, 2022)

First-order Policy Optimization for Robust Markov Decision Process. - Yan Li 074; Tuo Zhao; Guanghui Lan (CoRR, 2022)

First-order Policy Optimization for Robust Policy Evaluation. - Yan Li 074; Guanghui Lan (CoRR, 2023)

Block Policy Mirror Descent. - Guanghui Lan; Yan Li 074; Tuo Zhao (SIAM J. Optim., 2023)

Theories and Algorithms for Efficient and Robust Sequential Decision Making. - Yan Li 074 (2024)

Homotopic policy mirror descent: policy convergence, algorithmic regularization, and improved sample complexity. - Yan Li 074; Guanghui Lan; Tuo Zhao (Math. Program., 2024)

Policy Mirror Descent Inherently Explores Action Space. - Yan Li 074; Guanghui Lan (SIAM J. Optim., 2025)