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Runzhe Wu
Tytuł
Cytowane przez
Cytowane przez
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Malib: A parallel framework for population-based multi-agent reinforcement learning
M Zhou, Z Wan, H Wang, M Wen, R Wu, Y Wen, Y Yang, Y Yu, J Wang, ...
Journal of Machine Learning Research 24 (150), 1-12, 2023
622023
Making rl with preference-based feedback efficient via randomization
R Wu, W Sun
arXiv preprint arXiv:2310.14554, 2023
262023
The benefits of being distributional: Small-loss bounds for reinforcement learning
K Wang, K Zhou, R Wu, N Kallus, W Sun
Advances in neural information processing systems 36, 2275-2312, 2023
222023
Contextual bandits and imitation learning with preference-based active queries
A Sekhari, K Sridharan, W Sun, R Wu
Advances in Neural Information Processing Systems 36, 11261-11295, 2023
202023
Offline constrained multi-objective reinforcement learning via pessimistic dual value iteration
R Wu, Y Zhang, Z Yang, Z Wang
Advances in Neural Information Processing Systems 34, 25439-25451, 2021
202021
Distributional offline policy evaluation with predictive error guarantees
R Wu, M Uehara, W Sun
International Conference on Machine Learning, 37685-37712, 2023
192023
Selective sampling and imitation learning via online regression
A Sekhari, K Sridharan, W Sun, R Wu
Advances in Neural Information Processing Systems 36, 67213-67268, 2023
92023
Computationally efficient rl under linear bellman completeness for deterministic dynamics
R Wu, A Sekhari, A Krishnamurthy, W Sun
arXiv preprint arXiv:2406.11810, 2024
52024
Diffusing States and Matching Scores: A New Framework for Imitation Learning
R Wu, Y Chen, G Swamy, K Brantley, W Sun
arXiv preprint arXiv:2410.13855, 2024
32024
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