Xie, Qiaomin

27 publications

NeurIPS 2025 Contextual Online Pricing with (Biased) Offline Data Yixuan Zhang, Ruihao Zhu, Qiaomin Xie

AAAI 2025 Coupling-Based Convergence Diagnostic and Stepsize Scheme for Stochastic Gradient Descent Xiang Li, Qiaomin Xie

NeurIPS 2025 Offline Actor-Critic for Average Reward MDPs William Powell, Jeongyeol Kwon, Qiaomin Xie, Hanbaek Lyu

ICML 2025 Stable Offline Value Function Learning with Bisimulation-Based Representations Brahma S Pavse, Yudong Chen, Qiaomin Xie, Josiah P. Hanna

AISTATS 2025 Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way Jeongyeol Kwon, Luke Dotson, Yudong Chen, Qiaomin Xie

AAAI 2024 Data Poisoning to Fake a Nash Equilibria for Markov Games Young Wu, Jeremy McMahan, Xiaojin Zhu, Qiaomin Xie

AAAI 2024 Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference Dongyan Lucy Huo, Yudong Chen, Qiaomin Xie

AAAI 2024 Exact Policy Recovery in Offline RL with Both Heavy-Tailed Rewards and Data Corruption Yiding Chen, Xuezhou Zhang, Qiaomin Xie, Xiaojin Zhu

ICML 2024 Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces Brahma S Pavse, Matthew Zurek, Yudong Chen, Qiaomin Xie, Josiah P. Hanna

ICML 2024 Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value Young Wu, Jeremy Mcmahan, Yiding Chen, Yudong Chen, Jerry Zhu, Qiaomin Xie

AAAI 2024 Optimal Attack and Defense for Reinforcement Learning Jeremy McMahan, Young Wu, Xiaojin Zhu, Qiaomin Xie

ICML 2024 Roping in Uncertainty: Robustness and Regularization in Markov Games Jeremy Mcmahan, Giovanni Artiglio, Qiaomin Xie

AISTATS 2024 SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits Subhojyoti Mukherjee, Qiaomin Xie, Josiah P Hanna, Robert Nowak

AISTATS 2024 Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements Emmanouil Vasileios Vlatakis-Gkaragkounis, Angeliki Giannou, Yudong Chen, Qiaomin Xie

NeurIPS 2024 The Collusion of Memory and Nonlinearity in Stochastic Approximation with Constant Stepsize Dongyan Lucy Huo, Yixuan Zhang, Yudong Chen, Qiaomin Xie

NeurIPS 2023 Multi-Task Representation Learning for Pure Exploration in Bilinear Bandits Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna, Robert Nowak

NeurIPS 2023 Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption Yige Hong, Qiaomin Xie, Yudong Chen, Weina Wang

AAAI 2023 Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning Young Wu, Jeremy McMahan, Xiaojin Zhu, Qiaomin Xie

ICMLW 2023 SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits Subhojyoti Mukherjee, Qiaomin Xie, Josiah P. Hanna, Robert D Nowak

COLT 2023 Sharper Model-Free Reinforcement Learning for Average-Reward Markov Decision Processes Zihan Zhang, Qiaomin Xie

ICML 2021 Learning While Playing in Mean-Field Games: Convergence and Optimality Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca

NeurIPS 2020 Dynamic Regret of Policy Optimization in Non-Stationary Environments Yingjie Fei, Zhuoran Yang, Zhaoran Wang, Qiaomin Xie

COLT 2020 Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium Qiaomin Xie, Yudong Chen, Zhaoran Wang, Zhuoran Yang

NeurIPS 2020 POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis Weichao Mao, Kaiqing Zhang, Qiaomin Xie, Tamer Basar

NeurIPS 2020 Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang, Qiaomin Xie

L4DC 2020 Stable Reinforcement Learning with Unbounded State Space Devavrat Shah, Qiaomin Xie, Zhi Xu

NeurIPS 2018 Q-Learning with Nearest Neighbors Devavrat Shah, Qiaomin Xie