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2020 – today
- 2024
[c13]Yan Dai, Qiwen Cui, Simon S. Du:
Refined Sample Complexity for Markov Games with Independent Linear Function Approximation (Extended Abstract). COLT 2024: 1260-1261- [c12]Haozhe Jiang, Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon Shaolei Du:
A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning. ICLR 2024 - [c11]Zhaoyi Zhou, Chuning Zhu, Runlong Zhou, Qiwen Cui, Abhishek Gupta, Simon Shaolei Du:
Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning. ICLR 2024 - [i16]Yan Dai, Qiwen Cui, Simon S. Du:
Refined Sample Complexity for Markov Games with Independent Linear Function Approximation. CoRR abs/2402.07082 (2024) - [i15]Qiwen Cui, Maryam Fazel, Simon S. Du:
Learning Optimal Tax Design in Nonatomic Congestion Games. CoRR abs/2402.07437 (2024) - [i14]Yufeng Zhang, Liyu Chen, Boyi Liu, Yingxiang Yang, Qiwen Cui, Yunzhe Tao, Hongxia Yang:
(N, K)-Puzzle: A Cost-Efficient Testbed for Benchmarking Reinforcement Learning Algorithms in Generative Language Model. CoRR abs/2403.07191 (2024) - [i13]Natalia Zhang, Xinqi Wang, Qiwen Cui, Runlong Zhou, Sham M. Kakade, Simon S. Du:
Multi-Agent Reinforcement Learning from Human Feedback: Data Coverage and Algorithmic Techniques. CoRR abs/2409.00717 (2024) - 2023
- [j1]Minghan Yang, Dong Xu, Qiwen Cui
, Zaiwen Wen, Pengxiang Xu:
An Efficient Fisher Matrix Approximation Method for Large-Scale Neural Network Optimization. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5391-5403 (2023) - [c10]Qiwen Cui, Kaiqing Zhang, Simon S. Du:
Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation. COLT 2023: 2651-2652 - [c9]Haozhe Jiang, Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon Shaolei Du:
Offline Congestion Games: How Feedback Type Affects Data Coverage Requirement. ICLR 2023 - [i12]Qiwen Cui, Kaiqing Zhang, Simon S. Du:
Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation. CoRR abs/2302.03673 (2023) - [i11]Haozhe Jiang, Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon S. Du:
A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning. CoRR abs/2306.07465 (2023) - [i10]Zhaoyi Zhou, Chuning Zhu, Runlong Zhou, Qiwen Cui, Abhishek Gupta, Simon Shaolei Du:
Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning. CoRR abs/2310.19308 (2023) - 2022
- [c8]Qiwen Cui, Simon S. Du:
Provably Efficient Offline Multi-agent Reinforcement Learning via Strategy-wise Bonus. NeurIPS 2022 - [c7]Qiwen Cui, Simon S. Du:
When are Offline Two-Player Zero-Sum Markov Games Solvable? NeurIPS 2022 - [c6]Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon S. Du:
Learning in Congestion Games with Bandit Feedback. NeurIPS 2022 - [c5]Xinqi Wang, Qiwen Cui, Simon S. Du:
On Gap-dependent Bounds for Offline Reinforcement Learning. NeurIPS 2022 - [c4]Zhihan Xiong, Ruoqi Shen, Qiwen Cui, Maryam Fazel, Simon S. Du:
Near-Optimal Randomized Exploration for Tabular Markov Decision Processes. NeurIPS 2022 - [i9]Qiwen Cui, Simon S. Du:
When is Offline Two-Player Zero-Sum Markov Game Solvable? CoRR abs/2201.03522 (2022) - [i8]Qiwen Cui, Simon S. Du:
Provably Efficient Offline Multi-agent Reinforcement Learning via Strategy-wise Bonus. CoRR abs/2206.00159 (2022) - [i7]Xinqi Wang, Qiwen Cui, Simon S. Du:
On Gap-dependent Bounds for Offline Reinforcement Learning. CoRR abs/2206.00177 (2022) - [i6]Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon S. Du:
Learning in Congestion Games with Bandit Feedback. CoRR abs/2206.01880 (2022) - [i5]Haozhe Jiang, Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon S. Du:
Offline congestion games: How feedback type affects data coverage requirement. CoRR abs/2210.13396 (2022) - 2021
- [c3]Haque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin Yang:
Randomized Exploration in Reinforcement Learning with General Value Function Approximation. ICML 2021: 4607-4616 - [c2]Qiwen Cui, Lin F. Yang:
Minimax sample complexity for turn-based stochastic game. UAI 2021: 1496-1504 - [i4]Minghan Yang, Dong Xu, Qiwen Cui, Zaiwen Wen, Pengxiang Xu:
NG+ : A Multi-Step Matrix-Product Natural Gradient Method for Deep Learning. CoRR abs/2106.07454 (2021) - [i3]Haque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin F. Yang:
Randomized Exploration for Reinforcement Learning with General Value Function Approximation. CoRR abs/2106.07841 (2021) - 2020
- [c1]Qiwen Cui, Lin F. Yang:
Is Plug-in Solver Sample-Efficient for Feature-based Reinforcement Learning? NeurIPS 2020 - [i2]Qiwen Cui, Lin F. Yang:
Is Plug-in Solver Sample-Efficient for Feature-based Reinforcement Learning? CoRR abs/2010.05673 (2020) - [i1]Qiwen Cui, Lin F. Yang:
Minimax Sample Complexity for Turn-based Stochastic Game. CoRR abs/2011.14267 (2020)
Coauthor Index
aka: Simon Shaolei Du
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