Publications
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Making RL with Preference-based Feedback Efficient via Randomization
Runzhe Wu, Wen Sun
ICLR, 2024
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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]
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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)
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The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning
Kaiwen Wang, Kevin Zhou, Runzhe Wu, Nathan Kallus, Wen Sun
NeurIPS, 2023
[code]
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Distributional Offline Policy Evaluation with Predictive Error Guarantees
Runzhe Wu, Masatoshi Uehara, Wen Sun
ICML, 2023
[code]
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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]
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Offline Constrained Multi-Objective Reinforcement Learning via Pessimistic Dual Value
Iteration
Runzhe Wu, Yufeng Zhang, Zhuoran Yang, Zhaoran Wang
NeurIPS, 2021
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Invited Talk
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Computationally Efficient RL under Linear Bellman Completeness for Deterministic
Dynamics
@ RL Theory Seminar, Nov 19, 2024
 
[slides]
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Website template from here.
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