Runzhe Wu

I am a Computer Science Ph.D. student at Cornell University where I am advised by Wen Sun. I focus on reinforcement learning, exploring both its theory and practical applications.

Prior to Cornell, I obtained the Bachelor's degree from ACM Honors Class at Shanghai Jiao Tong University. While there, I engaged in research at the APEX Lab under the mentorship of Weinan Zhang and Yong Yu.

If you would like to chat with me, please drop me an email!

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Preprints
Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics
Runzhe Wu*, Ayush Sekhari*, Akshay Krishnamurthy, Wen Sun
ArXiv
Publications
Making RL with Preference-based Feedback Efficient via Randomization
Runzhe Wu, Wen Sun
ICLR, 2024
Contextual Bandits and Imitation Learning via Preference-Based Active Queries
(Alphabetical order) Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu
NeurIPS, 2023 (Also appeared at the ILHF & MFPL Workshop @ ICML, 2023)
[code]
Selective Sampling and Imitation Learning via Online Regression
(Alphabetical order) Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu
NeurIPS, 2023 (Also appeared at the ILHF Workshop @ ICML, 2023)
The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning
Kaiwen Wang, Kevin Zhou, Runzhe Wu, Nathan Kallus, Wen Sun
NeurIPS, 2023
[code]
Distributional Offline Policy Evaluation with Predictive Error Guarantees
Runzhe Wu, Masatoshi Uehara, Wen Sun
ICML, 2023
[code]
MALib: A parallel framework for population-based multi-agent reinforcement learning
Ming Zhou, Ziyu Wan, Hanjing Wang, Muning Wen, Runzhe Wu, Ying Wen, Yaodong Yang, Weinan Zhang, Jun Wang
JMLR, 2023
[website]   [code]
Offline Constrained Multi-Objective Reinforcement Learning via Pessimistic Dual Value Iteration
Runzhe Wu, Yufeng Zhang, Zhuoran Yang, Zhaoran Wang
NeurIPS, 2021
Education
Cornell University

Ph.D. in Computer Science

Aug. 2022 - Present

Shanghai Jiao Tong University

B.Eng. in Computer Science

Sep. 2018 - Jun. 2022



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