Offline Constrained Multi-Objective Reinforcement Learning via Pessimistic Dual Value Iteration. - Runzhe Wu; Yufeng Zhang 007; Zhuoran Yang; Zhaoran Wang 001 (NeurIPS, 2021)

MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning. - Ming Zhou 006; Ziyu Wan; Hanjing Wang; Muning Wen; Runzhe Wu; Ying Wen 001; Yaodong Yang 001; Weinan Zhang 001; Jun Wang 012 (CoRR, 2021)

Distributional Offline Policy Evaluation with Predictive Error Guarantees. - Runzhe Wu; Masatoshi Uehara; Wen Sun 002 (ICML, 2023)

Contextual Bandits and Imitation Learning with Preference-Based Active Queries. - Ayush Sekhari; Karthik Sridharan; Wen Sun 002; Runzhe Wu (NeurIPS, 2023)

Selective Sampling and Imitation Learning via Online Regression. - Ayush Sekhari; Karthik Sridharan; Wen Sun 002; Runzhe Wu (NeurIPS, 2023)

The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning. - Kaiwen Wang; Kevin Zhou; Runzhe Wu; Nathan Kallus; Wen Sun 002 (NeurIPS, 2023)

Contextual Bandits and Imitation Learning via Preference-Based Active Queries. - Ayush Sekhari; Karthik Sridharan; Wen Sun 002; Runzhe Wu (CoRR, 2023)

MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning. - Ming Zhou 006; Ziyu Wan; Hanjing Wang; Muning Wen; Runzhe Wu; Ying Wen 001; Yaodong Yang 001; Yong Yu 001; Jun Wang 012; Weinan Zhang 001 (J. Mach. Learn. Res., 2023)

Making RL with Preference-based Feedback Efficient via Randomization. - Runzhe Wu; Wen Sun 002 (ICLR, 2024)

Diffusing States and Matching Scores: A New Framework for Imitation Learning. - Runzhe Wu; Yiding Chen; Gokul Swamy; Kianté Brantley; Wen Sun 002 (ICLR, 2025)

Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics. - Runzhe Wu; Ayush Sekhari; Akshay Krishnamurthy; Wen Sun 002 (ICLR, 2025)