Yan Li - RankMe

26 papers A* 5A 2Journal 18

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Policy Mirror Descent Inherently Explores Action Space. SIAM J. Optim. Yan Li, Guanghui Lan
2024	J	`jnl`	Homotopic policy mirror descent: policy convergence, algorithmic regularization, and improved sample complexity. Math. Program. Yan Li, Guanghui Lan, Tuo Zhao
2024	—	`—`	Theories and Algorithms for Efficient and Robust Sequential Decision Making. Yan Li
2023	J	`jnl`	Block Policy Mirror Descent. SIAM J. Optim. Guanghui Lan, Yan Li, Tuo Zhao
2023	J	`jnl`	First-order Policy Optimization for Robust Policy Evaluation. CoRR Yan Li, Guanghui Lan
2023	J	`jnl`	Policy Mirror Descent Inherently Explores Action Space. CoRR Yan Li, Guanghui Lan
2022	J	`jnl`	Block Policy Mirror Descent. CoRR Guanghui Lan, Yan Li, Tuo Zhao
2022	J	`jnl`	Deep Learning Assisted End-to-End Synthesis of mm-Wave Passive Networks with 3D EM Structures: A Study on A Transformer-Based Matching Network. CoRR Siawpeng Er, Edward Liu, Minshuo Chen, Yan Li, Yuqi Liu, Tuo Zhao, Hua Wang
2022	J	`jnl`	First-order Policy Optimization for Robust Markov Decision Process. CoRR Yan Li, Tuo Zhao, Guanghui Lan
2022	A*	`conf`	Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. ICLR Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan
2022	J	`jnl`	Homotopic Policy Mirror Descent: Policy Convergence, Implicit Regularization, and Improved Sample Complexity. CoRR Yan Li, Tuo Zhao, Guanghui Lan
2022	A	`conf`	Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably. AISTATS Tianyi Liu, Yan Li, Enlu Zhou, Tuo Zhao
2022	J	`jnl`	Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably. CoRR Tianyi Liu, Yan Li, Enlu Zhou, Tuo Zhao
2021	J	`jnl`	Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. CoRR Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan
2021	J	`jnl`	Implicit Regularization of Bregman Proximal Point Algorithm and Mirror Descent on Separable Data. CoRR Yan Li, Caleb Ju, Ethan X. Fang, Tuo Zhao
2021	A	`conf`	Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization. AISTATS Tianyi Liu, Yan Li, Song Wei, Enlu Zhou, Tuo Zhao
2021	J	`jnl`	Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization. CoRR Tianyi Liu, Yan Li, Song Wei, Enlu Zhou, Tuo Zhao
2021	J	`jnl`	Permutation Invariant Policy Optimization for Mean-Field Multi-Agent Reinforcement Learning: A Principled Approach. CoRR Yan Li, Lingxiao Wang, Jiachen Yang, Ethan Wang, Zhaoran Wang, Tuo Zhao, Hongyuan Zha
2021	A*	`conf`	Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL. NeurIPS Minshuo Chen, Yan Li, Ethan Wang, Zhuoran Yang, Zhaoran Wang, Tuo Zhao
2020	A*	`conf`	Deep Reinforcement Learning with Robust and Smooth Policy. ICML Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao
2020	J	`jnl`	Deep Reinforcement Learning with Smooth Policy. CoRR Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao
2020	A*	`conf`	Implicit Bias of Gradient Descent based Adversarial Training on Separable Data. ICLR Yan Li, Ethan X. Fang, Huan Xu, Tuo Zhao
2020	J	`jnl`	Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers. CoRR David Joseph Munzer, Siawpeng Er, Minshuo Chen, Yan Li, Naga Sasikanth Mannem, Tuo Zhao, Hua Wang
2019	J	`jnl`	Inductive Bias of Gradient Descent based Adversarial Training on Separable Data. CoRR Yan Li, Ethan X. Fang, Huan Xu, Tuo Zhao
2019	A*	`conf`	Toward Understanding the Importance of Noise in Training Neural Networks. ICML Mo Zhou, Tianyi Liu, Yan Li, Dachao Lin, Enlu Zhou, Tuo Zhao
2019	J	`jnl`	Towards Understanding the Importance of Noise in Training Neural Networks. CoRR Mo Zhou, Tianyi Liu, Yan Li, Dachao Lin, Enlu Zhou, Tuo Zhao