Han Zhong

Publication Activity (10 Years)

Years Active: 2022-2024
Publications (10 Years): 15

Top Topics

Function Approximation

Markov Decision Process

Nash Equilibria

Reinforcement Learning

Top Venues

Publications

Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang
Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation. AISTATS (2024)
Miao Lu, Han Zhong, Tong Zhang, Jose H. Blanchet
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm. CoRR (2024)
Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang
Towards Robust Offline Reinforcement Learning under Diverse Data Corruption. ICLR (2024)
Jiachen Hu, Tongyang Li, Xinzhao Wang, Yecheng Xue, Chenyi Zhang, Han Zhong
Quantum Non-Identical Mean Estimation: Efficient Algorithms and Fundamental Limits. TQC (2024)
Zhihan Liu, Miao Lu, Wei Xiong, Han Zhong, Hao Hu, Shenao Zhang, Sirui Zheng, Zhuoran Yang, Zhaoran Wang
One Objective to Rule Them All: A Maximization Objective Fusing Estimation and Planning for Exploration. CoRR (2023)
Yunchang Yang, Han Zhong, Tianhao Wu, Bin Liu, Liwei Wang, Simon S. Du
A Reduction-based Framework for Sequential Decision Making with Delayed Feedback. NeurIPS (2023)
Jiayi Huang, Han Zhong, Liwei Wang, Lin F. Yang
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds. CoRR (2023)
Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds. NeurIPS (2023)
Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang, Tong Zhang
Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game. ICLR (2023)
Jiachen Hu, Han Zhong, Chi Jin, Liwei Wang
Provable Sim-to-real Transfer in Continuous Domain with Partial Observations. ICLR (2023)
Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang
Posterior Sampling for Competitive RL: Function Approximation and Partial Observation. NeurIPS (2023)
Han Zhong, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan
Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopically Rational Followers? J. Mach. Learn. Res. 24 (2023)
Han Zhong, Tong Zhang
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes. NeurIPS (2023)
Jiayi Huang, Han Zhong, Liwei Wang, Lin F. Yang
Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation. CoRR (2023)
Binghui Li, Jikai Jin, Han Zhong, John E. Hopcroft, Liwei Wang
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power. NeurIPS (2022)