Han Zhong - RankMe

59 papers A* 24A 1Journal 33Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Muon in Associative Memory Learning: Training Dynamics and Scaling Laws. CoRR Binghui Li, Kaifei Wang, Han Zhong, Pinyan Lu, Liwei Wang
2026	J	`jnl`	Robust Assortment Optimization from Observational Data. CoRR Miao Lu, Yuxuan Han, Han Zhong, Zhengyuan Zhou, Jose H. Blanchet
2025	A*	`conf`	BRiTE: Bootstrapping Reinforced Thinking Process to Enhance Language Model Reasoning. ICML Han Zhong, Yutong Yin, Shenao Zhang, Xiaojun Xu, Yuanxin Liu, Yifei Zuo, Zhihan Liu, Boyi Liu, Sirui Zheng, Hongyi Guo, Liwei Wang, Mingyi Hong, Zhaoran Wang
2025	J	`jnl`	BRiTE: Bootstrapping Reinforced Thinking Process to Enhance Language Model Reasoning. CoRR Han Zhong, Yutong Yin, Shenao Zhang, Xiaojun Xu, Yuanxin Liu, Yifei Zuo, Zhihan Liu, Boyi Liu, Sirui Zheng, Hongyi Guo, Liwei Wang, Mingyi Hong, Zhaoran Wang
2025	A*	`conf`	DPO Meets PPO: Reinforced Token Optimization for RLHF. ICML Han Zhong, Zikang Shan, Guhao Feng, Wei Xiong, Xinle Cheng, Li Zhao, Di He, Jiang Bian, Liwei Wang
2025	J	`jnl`	Learning an Optimal Assortment Policy under Observational Data. CoRR Yuxuan Han, Han Zhong, Miao Lu, Jose H. Blanchet, Zhengyuan Zhou
2025	J	`jnl`	Self-Exploring Language Models: Active Preference Elicitation for Online Alignment. Trans. Mach. Learn. Res. Shenao Zhang, Donghan Yu, Hiteshi Sharma, Han Zhong, Zhihan Liu, Ziyi Yang, Shuohang Wang, Hany Hassan Awadalla, Zhaoran Wang
2025	A*	`conf`	The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability. ICML Jiachen Hu, Rui Ai, Han Zhong, Xiaoyu Chen, Liwei Wang, Zhaoran Wang, Zhuoran Yang
2025	J	`jnl`	The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability. CoRR Jiachen Hu, Rui Ai, Han Zhong, Xiaoyu Chen, Liwei Wang, Zhaoran Wang, Zhuoran Yang
2024	J	`jnl`	DPO Meets PPO: Reinforced Token Optimization for RLHF. CoRR Han Zhong, Guhao Feng, Wei Xiong, Li Zhao, Di He, Jiang Bian, Liwei Wang
2024	J	`jnl`	Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm. CoRR Miao Lu, Han Zhong, Tong Zhang, Jose H. Blanchet
2024	A*	`conf`	Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms. NeurIPS Miao Lu, Han Zhong, Tong Zhang, Jose H. Blanchet
2024	A	`conf`	Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation. AISTATS Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang
2024	A*	`conf`	Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint. ICML Wei Xiong, Hanze Dong, Chenlu Ye, Ziqi Wang, Han Zhong, Heng Ji, Nan Jiang, Tong Zhang
2024	A*	`conf`	Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret. ICML Han Zhong, Jiachen Hu, Yecheng Xue, Tongyang Li, Liwei Wang
2024	—	`conf`	Quantum Non-Identical Mean Estimation: Efficient Algorithms and Fundamental Limits. TQC Jiachen Hu, Tongyang Li, Xinzhao Wang, Yecheng Xue, Chenyi Zhang, Han Zhong
2024	A*	`conf`	Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity. NeurIPS Guhao Feng, Han Zhong
2024	A*	`conf`	Rewards-in-Context: Multi-objective Alignment of Foundation Models with Dynamic Preference Adjustment. ICML Rui Yang, Xiaoman Pan, Feng Luo, Shuang Qiu, Han Zhong, Dong Yu, Jianshu Chen
2024	J	`jnl`	Rewards-in-Context: Multi-objective Alignment of Foundation Models with Dynamic Preference Adjustment. CoRR Rui Yang, Xiaoman Pan, Feng Luo, Shuang Qiu, Han Zhong, Dong Yu, Jianshu Chen
2024	A*	`conf`	Towards Robust Offline Reinforcement Learning under Diverse Data Corruption. ICLR Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang
2023	A*	`conf`	A Reduction-based Framework for Sequential Decision Making with Delayed Feedback. NeurIPS Yunchang Yang, Han Zhong, Tianhao Wu, Bin Liu, Liwei Wang, Simon S. Du
2023	J	`jnl`	A Reduction-based Framework for Sequential Decision Making with Delayed Feedback. CoRR Yunchang Yang, Han Zhong, Tianhao Wu, Bin Liu, Liwei Wang, Simon S. Du
2023	A*	`conf`	A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes. NeurIPS Han Zhong, Tong Zhang
2023	J	`jnl`	A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes. CoRR Han Zhong, Tong Zhang
2023	J	`jnl`	Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopically Rational Followers? J. Mach. Learn. Res. Han Zhong, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan
2023	A*	`conf`	Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage. NeurIPS Jose H. Blanchet, Miao Lu, Tong Zhang, Han Zhong
2023	J	`jnl`	Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage. CoRR Jose H. Blanchet, Miao Lu, Tong Zhang, Han Zhong
2023	J	`jnl`	Gibbs Sampling from Human Feedback: A Provable KL- constrained Framework for RLHF. CoRR Wei Xiong, Hanze Dong, Chenlu Ye, Han Zhong, Nan Jiang, Tong Zhang
2023	J	`jnl`	Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation. CoRR Jiayi Huang, Han Zhong, Liwei Wang, Lin F. Yang
2023	A*	`conf`	Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration. NeurIPS Zhihan Liu, Miao Lu, Wei Xiong, Han Zhong, Hao Hu, Shenao Zhang, Sirui Zheng, Zhuoran Yang, Zhaoran Wang
2023	A*	`conf`	Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game. ICLR Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang, Tong Zhang
2023	J	`jnl`	One Objective to Rule Them All: A Maximization Objective Fusing Estimation and Planning for Exploration. CoRR Zhihan Liu, Miao Lu, Wei Xiong, Han Zhong, Hao Hu, Shenao Zhang, Sirui Zheng, Zhuoran Yang, Zhaoran Wang
2023	A*	`conf`	Posterior Sampling for Competitive RL: Function Approximation and Partial Observation. NeurIPS Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang
2023	J	`jnl`	Posterior Sampling for Competitive RL: Function Approximation and Partial Observation. CoRR Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang
2023	A*	`conf`	Provable Sim-to-real Transfer in Continuous Domain with Partial Observations. ICLR Jiachen Hu, Han Zhong, Chi Jin, Liwei Wang
2023	J	`jnl`	Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret. CoRR Han Zhong, Jiachen Hu, Yecheng Xue, Tongyang Li, Liwei Wang
2023	A*	`conf`	Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds. NeurIPS Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang
2023	J	`jnl`	Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds. CoRR Jiayi Huang, Han Zhong, Liwei Wang, Lin F. Yang
2023	J	`jnl`	Towards Robust Offline Reinforcement Learning under Diverse Data Corruption. CoRR Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang
2022	A*	`conf`	A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning. ICLR Yunchang Yang, Tianhao Wu, Han Zhong, Evrard Garcelon, Matteo Pirotta, Alessandro Lazaric, Liwei Wang, Simon Shaolei Du
2022	A*	`conf`	A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games. ICML Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang
2022	J	`jnl`	A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games. CoRR Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang
2022	J	`jnl`	GEC: A Unified Framework for Interactive Decision Making in MDP, POMDP, and Beyond. CoRR Han Zhong, Wei Xiong, Sirui Zheng, Liwei Wang, Zhaoran Wang, Zhuoran Yang, Tong Zhang
2022	A*	`conf`	Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation. ICML Xiaoyu Chen, Han Zhong, Zhuoran Yang, Zhaoran Wang, Liwei Wang
2022	J	`jnl`	Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation. CoRR Xiaoyu Chen, Han Zhong, Zhuoran Yang, Zhaoran Wang, Liwei Wang
2022	J	`jnl`	Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game. CoRR Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang, Tong Zhang
2022	A*	`conf`	Nearly Optimal Policy Optimization with Stable at Any Time Guarantee. ICML Tianhao Wu, Yunchang Yang, Han Zhong, Liwei Wang, Simon S. Du, Jiantao Jiao
2022	A*	`conf`	Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets. ICML Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang
2022	J	`jnl`	Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets. CoRR Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang
2022	J	`jnl`	Provable Sim-to-real Transfer in Continuous Domain with Partial Observations. CoRR Jiachen Hu, Han Zhong, Chi Jin, Liwei Wang
2022	A*	`conf`	Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power. NeurIPS Binghui Li, Jikai Jin, Han Zhong, John E. Hopcroft, Liwei Wang
2022	J	`jnl`	Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power. CoRR Binghui Li, Jikai Jin, Han Zhong, John E. Hopcroft, Liwei Wang
2021	J	`jnl`	A Unified Framework for Conservative Exploration. CoRR Yunchang Yang, Tianhao Wu, Han Zhong, Evrard Garcelon, Matteo Pirotta, Alessandro Lazaric, Liwei Wang, Simon S. Du
2021	A*	`conf`	Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs. NeurIPS Han Zhong, Jiayi Huang, Lin Yang, Liwei Wang
2021	J	`jnl`	Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs. CoRR Han Zhong, Jiayi Huang, Lin F. Yang, Liwei Wang
2021	J	`jnl`	Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers? CoRR Han Zhong, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan
2021	J	`jnl`	Nearly Optimal Policy Optimization with Stable at Any Time Guarantee. CoRR Tianhao Wu, Yunchang Yang, Han Zhong, Liwei Wang, Simon S. Du, Jiantao Jiao
2021	J	`jnl`	Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPs. CoRR Han Zhong, Zhuoran Yang, Zhaoran Wang, Csaba Szepesvári
2020	J	`jnl`	Risk-Sensitive Deep RL: Variance-Constrained Actor-Critic Provably Finds Globally Optimal Policy. CoRR Han Zhong, Ethan X. Fang, Zhuoran Yang, Zhaoran Wang