Chen-Yu Wei

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 80

Top Topics

Policy Gradient

Function Approximation

Reinforcement Learning

Top Venues

Publications

Haolin Liu, Chen-Yu Wei, Julian Zimmert
Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback. ICLR (2024)
Yang Cai, Constantinos Daskalakis, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng
Tractable Local Equilibria in Non-Concave Games. CoRR (2024)
Zeyu Jia, Alexander Rakhlin, Ayush Sekhari, Chen-Yu Wei
Offline Reinforcement Learning: Role of State Aggregation and Trajectory Data. COLT (2024)
Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng
Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games. AISTATS (2024)
Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng
Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games. CoRR (2024)
Zeyu Jia, Alexander Rakhlin, Ayush Sekhari, Chen-Yu Wei
Offline Reinforcement Learning: Role of State Aggregation and Trajectory Data. CoRR (2024)
Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Alejandro Ribeiro
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs. CoRR (2023)
Haolin Liu, Chen-Yu Wei, Julian Zimmert
Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits. NeurIPS (2023)
Christoph Dann, Chen-Yu Wei, Julian Zimmert
A Blackbox Approach to Best of Both Worlds in Bandits and Beyond. COLT (2023)
Yan Dai, Haipeng Luo, Chen-Yu Wei, Julian Zimmert
Refined Regret for Adversarial MDPs with Linear Function Approximation. ICML (2023)
Christoph Dann, Chen-Yu Wei, Julian Zimmert
Best of Both Worlds Policy Optimization. CoRR (2023)
Christoph Dann, Chen-Yu Wei, Julian Zimmert
A Unified Algorithm for Stochastic Path Problems. ALT (2023)
Julia Olkhovskaya, Jack J. Mayo, Tim van Erven, Gergely Neu, Chen-Yu Wei
First- and Second-Order Bounds for Adversarial Linear Contextual Bandits. NeurIPS (2023)
Tiancheng Jin, Junyan Liu, Chloé Rouyer, William Chang, Chen-Yu Wei, Haipeng Luo
No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions. NeurIPS (2023)
Julia Olkhovskaya, Jack J. Mayo, Tim van Erven, Gergely Neu, Chen-Yu Wei
First- and Second-Order Bounds for Adversarial Linear Contextual Bandits. CoRR (2023)
Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Alejandro Ribeiro
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs. NeurIPS (2023)
Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games. CoRR (2023)
Yan Dai, Haipeng Luo, Chen-Yu Wei, Julian Zimmert
Refined Regret for Adversarial MDPs with Linear Function Approximation. CoRR (2023)
Haolin Liu, Chen-Yu Wei, Julian Zimmert
Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback. CoRR (2023)
Tiancheng Jin, Junyan Liu, Chloé Rouyer, William Chang, Chen-Yu Wei, Haipeng Luo
No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions. CoRR (2023)
Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback. NeurIPS (2023)
Christoph Dann, Chen-Yu Wei, Julian Zimmert
A Blackbox Approach to Best of Both Worlds in Bandits and Beyond. CoRR (2023)
Haolin Liu, Chen-Yu Wei, Julian Zimmert
Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits. CoRR (2023)
Christoph Dann, Chen-Yu Wei, Julian Zimmert
Best of Both Worlds Policy Optimization. ICML (2023)
Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Mihailo R. Jovanovic
Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence. CoRR (2022)
Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Mihailo R. Jovanovic
Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence. ICML (2022)
Alberto Bietti, Chen-Yu Wei, Miroslav Dudík, John Langford, Zhiwei Steven Wu
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning. ICML (2022)
Hsu Kao, Chen-Yu Wei, Vijay G. Subramanian
Decentralized Cooperative Reinforcement Learning with Hierarchical Information Structure. ALT (2022)
Christoph Dann, Chen-Yu Wei, Julian Zimmert
A Unified Algorithm for Stochastic Path Problems. CoRR (2022)
Chen-Yu Wei, Christoph Dann, Julian Zimmert
A Model Selection Approach for Corruption Robust Reinforcement Learning. ALT (2022)
Alberto Bietti, Chen-Yu Wei, Miroslav Dudík, John Langford, Zhiwei Steven Wu
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Optimization. CoRR (2022)
Haipeng Luo, Chen-Yu Wei, Chung-Wei Lee
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses. NeurIPS (2021)
Chen-Yu Wei, Haipeng Luo
Non-stationary Reinforcement Learning without Prior Knowledge: An Optimal Black-box Approach. CoRR (2021)
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously. ICML (2021)
Haipeng Luo, Chen-Yu Wei, Chung-Wei Lee
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses. CoRR (2021)
Hsu Kao, Chen-Yu Wei, Vijay G. Subramanian
Decentralized Cooperative Reinforcement Learning with Hierarchical Information Structure. CoRR (2021)
Ehsan Emamjomeh-Zadeh, Chen-Yu Wei, Haipeng Luo, David Kempe
Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds. ALT (2021)
Liyu Chen, Haipeng Luo, Chen-Yu Wei
Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition. COLT (2021)
Liyu Chen, Haipeng Luo, Chen-Yu Wei
Impossible Tuning Made Possible: A New Expert Algorithm and Its Applications. COLT (2021)
Liyu Chen, Haipeng Luo, Chen-Yu Wei
Impossible Tuning Made Possible: A New Expert Algorithm and Its Applications. CoRR (2021)
Chen-Yu Wei, Chung-Wei Lee, Mengxiao Zhang, Haipeng Luo
Last-iterate Convergence of Decentralized Optimistic Gradient Descent/Ascent in Infinite-horizon Competitive Markov Games. CoRR (2021)
Chen-Yu Wei, Christoph Dann, Julian Zimmert
A Model Selection Approach for Corruption Robust Reinforcement Learning. CoRR (2021)
Chen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo, Rahul Jain
Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation. AISTATS (2021)
Chen-Yu Wei, Chung-Wei Lee, Mengxiao Zhang, Haipeng Luo
Linear Last-iterate Convergence in Constrained Saddle-point Optimization. ICLR (2021)
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously. CoRR (2021)
Chen-Yu Wei, Chung-Wei Lee, Mengxiao Zhang, Haipeng Luo
Last-iterate Convergence of Decentralized Optimistic Gradient Descent/Ascent in Infinite-horizon Competitive Markov Games. COLT (2021)
Chen-Yu Wei, Haipeng Luo
Non-stationary Reinforcement Learning without Prior Knowledge: an Optimal Black-box Approach. COLT (2021)
Chen-Yu Wei, Haipeng Luo, Alekh Agarwal
Taking a hint: How to leverage loss predictors in contextual bandits? CoRR (2020)
Chen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo, Rahul Jain
Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation. CoRR (2020)
Chen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo, Hiteshi Sharma, Rahul Jain
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes. ICML (2020)
Ehsan Emamjomeh-Zadeh, Chen-Yu Wei, Haipeng Luo, David Kempe
Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds. CoRR (2020)
Chen-Yu Wei, Haipeng Luo, Alekh Agarwal
Taking a hint: How to leverage loss predictors in contextual bandits? COLT (2020)
Mehdi Jafarnia-Jahromi, Chen-Yu Wei, Rahul Jain, Haipeng Luo
A Model-free Learning Algorithm for Infinite-horizon Average-reward MDPs with Near-optimal Regret. CoRR (2020)
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang
Bias no more: high-probability data-dependent regret bounds for adversarial bandits and MDPs. CoRR (2020)
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang
Bias no more: high-probability data-dependent regret bounds for adversarial bandits and MDPs. NeurIPS (2020)
Liyu Chen, Haipeng Luo, Chen-Yu Wei
Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition. CoRR (2020)
Alekh Agarwal, John Langford, Chen-Yu Wei
Federated Residual Learning. CoRR (2020)
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang
Linear Last-iterate Convergence for Matrix Games and Stochastic Games. CoRR (2020)
James A. Preiss, Sébastien M. R. Arnold, Chen-Yu Wei, Marius Kloft
Analyzing the Variance of Policy Gradient Estimators for the Linear-Quadratic Regulator. CoRR (2019)
Sébastien Bubeck, Yuanzhi Li, Haipeng Luo, Chen-Yu Wei
Improved Path-length Regret Bounds for Bandits. CoRR (2019)
Julian Zimmert, Haipeng Luo, Chen-Yu Wei
Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously. ICML (2019)
Julian Zimmert, Haipeng Luo, Chen-Yu Wei
Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously. CoRR (2019)
Peter Auer, Yifang Chen, Pratik Gajane, Chung-Wei Lee, Haipeng Luo, Ronald Ortner, Chen-Yu Wei
Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information. COLT (2019)
Alina Beygelzimer, Dávid Pál, Balázs Szörényi, Devanathan Thiruvenkatachari, Chen-Yu Wei, Chicheng Zhang
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case. CoRR (2019)
Yifang Chen, Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei
A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal and Parameter-free. COLT (2019)
Chen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo, Hiteshi Sharma, Rahul Jain
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes. CoRR (2019)
Alina Beygelzimer, Dávid Pál, Balázs Szörényi, Devanathan Thiruvenkatachari, Chen-Yu Wei, Chicheng Zhang
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case. ICML (2019)
Sébastien Bubeck, Yuanzhi Li, Haipeng Luo, Chen-Yu Wei
Improved Path-length Regret Bounds for Bandits. COLT (2019)
Yifang Chen, Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei
A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal, and Parameter-free. CoRR (2019)
Haipeng Luo, Chen-Yu Wei, Kai Zheng
Efficient Online Portfolio with Logarithmic Regret. NeurIPS (2018)
Chen-Yu Wei, Haipeng Luo
More Adaptive Algorithms for Adversarial Bandits. COLT (2018)
Chen-Yu Wei, Wanjiun Liao
Multi-Cell Cooperative Scheduling for Network Utility Maximization With User Equipment Side Interference Cancellation. IEEE Trans. Wirel. Commun. 17 (1) (2018)
Haipeng Luo, Chen-Yu Wei, Kai Zheng
Efficient Online Portfolio with Logarithmic Regret. CoRR (2018)
Chen-Yu Wei, Haipeng Luo
More Adaptive Algorithms for Adversarial Bandits. CoRR (2018)
Haipeng Luo, Chen-Yu Wei, Alekh Agarwal, John Langford
Efficient Contextual Bandits in Non-stationary Worlds. COLT (2018)
Chen-Yu Wei, Yi-Te Hong, Chi-Jen Lu
Tracking the Best Expert in Non-stationary Stochastic Environments. CoRR (2017)
Chen-Yu Wei, Yi-Te Hong, Chi-Jen Lu
Online Reinforcement Learning in Stochastic Games. CoRR (2017)
Chen-Yu Wei, Yi-Te Hong, Chi-Jen Lu
Online Reinforcement Learning in Stochastic Games. NIPS (2017)
Chen-Yu Wei, Yi-Te Hong, Chi-Jen Lu
Tracking the Best Expert in Non-stationary Stochastic Environments. NIPS (2016)
Hsu Kao, Chen-Yu Wei, Hsiao-Ching Lin, Yi-Han Chiang, Wanjiun Liao
Adaptive measurement for energy efficient mobility management in ultra-dense small cell networks. ICC (2016)