Yu, Tiancheng

13 publications

ICLR 2023 The Power of Regularization in Solving Extensive-Form Games Mingyang Liu, Asuman E. Ozdaglar, Tiancheng Yu, Kaiqing Zhang

NeurIPS 2022 Efficient Phi-Regret Minimization in Extensive-Form Games via Online Mirror Descent Yu Bai, Chi Jin, Song Mei, Ziang Song, Tiancheng Yu

ICML 2022 Near-Optimal Learning of Extensive-Form Games with Imperfect Information Yu Bai, Chi Jin, Song Mei, Tiancheng Yu

ICLRW 2022 Near-Optimal Learning of Extensive-Form Games with Imperfect Information Yu Bai, Chi Jin, Song Mei, Tiancheng Yu

ICML 2022 The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces Chi Jin, Qinghua Liu, Tiancheng Yu

ICLRW 2022 V-Learning -- a Simple, Efficient, Decentralized Algorithm for Multiagent RL Chi Jin, Qinghua Liu, Yuanhao Wang, Tiancheng Yu

ICML 2021 A Sharp Analysis of Model-Based Reinforcement Learning with Self-Play Qinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin

ICML 2021 Online Learning in Unknown Markov Games Yi Tian, Yuanhao Wang, Tiancheng Yu, Suvrit Sra

ICML 2021 Provably Efficient Algorithms for Multi-Objective Competitive RL Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra

ICML 2020 Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition Chi Jin, Tiancheng Jin, Haipeng Luo, Suvrit Sra, Tiancheng Yu

NeurIPS 2020 Near-Optimal Reinforcement Learning with Self-Play Yu Bai, Chi Jin, Tiancheng Yu

ICML 2020 Reward-Free Exploration for Reinforcement Learning Chi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu

NeurIPS 2018 Entropy Rate Estimation for Markov Chains with Large State Space Yanjun Han, Jiantao Jiao, Chuan-Zheng Lee, Tsachy Weissman, Yihong Wu, Tiancheng Yu