Is Plug-in Solver Sample-Efficient for Feature-based Reinforcement Learning? - Qiwen Cui; Lin F. Yang (NeurIPS, 2020)

Randomized Exploration in Reinforcement Learning with General Value Function Approximation. - Haque Ishfaq; Qiwen Cui; Viet Nguyen; Alex Ayoub; Zhuoran Yang; Zhaoran Wang 001; Doina Precup; Lin Yang 011 (ICML, 2021)

Minimax sample complexity for turn-based stochastic game. - Qiwen Cui; Lin F. Yang (UAI, 2021)

NG+ : A Multi-Step Matrix-Product Natural Gradient Method for Deep Learning. - Minghan Yang; Dong Xu; Qiwen Cui; Zaiwen Wen; Pengxiang Xu (CoRR, 2021)

Provably Efficient Offline Multi-agent Reinforcement Learning via Strategy-wise Bonus. - Qiwen Cui; Simon S. Du (NeurIPS, 2022)

When are Offline Two-Player Zero-Sum Markov Games Solvable? - Qiwen Cui; Simon S. Du (NeurIPS, 2022)

Learning in Congestion Games with Bandit Feedback. - Qiwen Cui; Zhihan Xiong; Maryam Fazel; Simon S. Du (NeurIPS, 2022)

On Gap-dependent Bounds for Offline Reinforcement Learning. - Xinqi Wang; Qiwen Cui; Simon S. Du (NeurIPS, 2022)

Near-Optimal Randomized Exploration for Tabular Markov Decision Processes. - Zhihan Xiong; Ruoqi Shen; Qiwen Cui; Maryam Fazel; Simon S. Du (NeurIPS, 2022)

When is Offline Two-Player Zero-Sum Markov Game Solvable? - Qiwen Cui; Simon S. Du (CoRR, 2022)

Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation. - Qiwen Cui; Kaiqing Zhang; Simon S. Du (COLT, 2023)

Offline Congestion Games: How Feedback Type Affects Data Coverage Requirement. - Haozhe Jiang; Qiwen Cui; Zhihan Xiong; Maryam Fazel; Simon Shaolei Du (ICLR, 2023)

An Efficient Fisher Matrix Approximation Method for Large-Scale Neural Network Optimization. - Minghan Yang; Dong Xu; Qiwen Cui; Zaiwen Wen; Pengxiang Xu (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Refined Sample Complexity for Markov Games with Independent Linear Function Approximation (Extended Abstract). - Yan Dai 002; Qiwen Cui; Simon S. Du (COLT, 2024)

A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning. - Haozhe Jiang; Qiwen Cui; Zhihan Xiong; Maryam Fazel; Simon Shaolei Du (ICLR, 2024)

Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning. - Zhaoyi Zhou; Chuning Zhu; Runlong Zhou; Qiwen Cui; Abhishek Gupta 004; Simon Shaolei Du (ICLR, 2024)

Learning Optimal Tax Design in Nonatomic Congestion Games. - Qiwen Cui; Maryam Fazel; Simon S. Du (NeurIPS, 2024)

Refined Sample Complexity for Markov Games with Independent Linear Function Approximation. - Yan Dai 002; Qiwen Cui; Simon S. Du (CoRR, 2024)

(N, K)-Puzzle: A Cost-Efficient Testbed for Benchmarking Reinforcement Learning Algorithms in Generative Language Model. - Yufeng Zhang; Liyu Chen; Boyi Liu; Yingxiang Yang; Qiwen Cui; Yunzhe Tao; Hongxia Yang (CoRR, 2024)

Multi-Agent Reinforcement Learning from Human Feedback: Data Coverage and Algorithmic Techniques. - Natalia Zhang; Xinqi Wang; Qiwen Cui; Runlong Zhou; Sham M. Kakade; Simon S. Du (CoRR, 2024)

BabelBench: An Omni Benchmark for Code-Driven Analysis of Multimodal and Multistructured Data. - Xuwu Wang; Qiwen Cui; Yunzhe Tao; Yiran Wang; Ziwei Chai; Xiaotian Han; Boyi Liu; Jianbo Yuan; Jing Su; Guoyin Wang 002; Tingkai Liu; Liyu Chen; et al. (CoRR, 2024)