Jia, Zeyu

14 publications

ICML 2025 Do We Need to Verify Step by Step? Rethinking Process Supervision from a Theoretical Perspective Zeyu Jia, Alexander Rakhlin, Tengyang Xie

COLT 2025 On the Minimax Regret of Sequential Probability Assignment via Square-Root Entropy Zeyu Jia, Alexander Rakhlin, Yury Polyanskiy

NeurIPS 2025 Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits Fan Chen, Zeyu Jia, Alexander Rakhlin, Tengyang Xie

NeurIPS 2025 Trajectory Bellman Residual Minimization: A Simple Value-Based Method for LLM Reasoning Yurun Yuan, Fan Chen, Zeyu Jia, Alexander Rakhlin, Tengyang Xie

NeurIPS 2024 How Does Variance Shape the Regret in Contextual Bandits? Zeyu Jia, Jian Qian, Alexander Rakhlin, Chen-Yu Wei

COLT 2024 Offline Reinforcement Learning: Role of State Aggregation and Trajectory Data Zeyu Jia, Alexander Rakhlin, Ayush Sekhari, Chen-Yu Wei

COLT 2023 Entropic Characterization of Optimal Rates for Learning Gaussian Mixtures Zeyu Jia, Yury Polyanskiy, Yihong Wu

ALT 2023 Linear Reinforcement Learning with Ball Structure Action Space Zeyu Jia, Randy Jia, Dhruv Madeka, Dean P. Foster

NeurIPS 2023 When Is Agnostic Reinforcement Learning Statistically Tractable? Zeyu Jia, Gene Li, Alexander Rakhlin, Ayush Sekhari, Nati Srebro

ICMLW 2023 When Is Agnostic Reinforcement Learning Statistically Tractable? Gene Li, Zeyu Jia, Alexander Rakhlin, Ayush Sekhari, Nathan Srebro

JMLR 2022 Intrinsic Dimension Estimation Using Wasserstein Distance Adam Block, Zeyu Jia, Yury Polyanskiy, Alexander Rakhlin

ICML 2020 Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation Yaqi Duan, Zeyu Jia, Mengdi Wang

ICML 2020 Model-Based Reinforcement Learning with Value-Targeted Regression Alex Ayoub, Zeyu Jia, Csaba Szepesvari, Mengdi Wang, Lin Yang

L4DC 2020 Model-Based Reinforcement Learning with Value-Targeted Regression Zeyu Jia, Lin Yang, Csaba Szepesvari, Mengdi Wang