Publication

*: indicating equal contribution.

2024

• Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning.
  Fan-Ming Luo, Tian Xu, Xingchen Cao, Yang Yu
  In Proceedings of the 12th International Conference on Learning Representations (ICLR, spotlight, acceptance rate < 5% ), 2024

• Policy Rehearsing: Training Generalizable Policies for Reinforcement Learning
  Chengxing Jia, Chenxiao Gao, Hao Yin, Fuxiang Zhang, Xiong-Hui Chen, Tian Xu, Lei Yuan, Zongzhang Zhang, Yang Yu, Zhi-Hua Zhou
  In Proceedings of the 12th International Conference on Learning Representations (ICLR), 2024

2023

• Policy Optimization in RLHF: The Impact of Out-of-preference Data.
  Ziniu Li, Tian Xu*, Yang Yu.

• ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models.
  Ziniu Li, Tian Xu, Yushun Zhang, Yang Yu, Ruoyu Sun, Zhi-Quan Luo
  

• Imitation Learning from Imperfection: Theoretical Justifications and Algorithms.
  Ziniu Li*, Tian Xu*, Zeyu Qin, Yang Yu, Zhi-Quan Luo
  In Advances in Neural Information Process System 36 (NeurIPS, spotlight, acceptance rate < 5 % ), 2023.
  An early version is accepted in DMLR Workshop: Data-centric Machine Learning Research in ICML 2023.

• Model Gradient: Unified Model and Policy Learning in Model-based Reinforcement Learning.
  Chengxing Jia*, Fuxiang Zhang*, Tian Xu, Jing-Cheng Pang, Zongzhang Zhang, Yang Yu.
  Frontiers of Computer Science, 2023.

• Provably Efficient Adversarial Imitation Learning with Unknown Transitions [Poster] [Video] [Oral Slides]
  Tian Xu*, Ziniu Li*, Yang Yu, Zhi-Quan Luo
  In Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence (UAI, oral presentation, acceptance rate < 3% ), 2023
  

• A Survey on Model-based Reinforcement Learning
  Fan-Ming Luo, Tian Xu, Hang Lai, Xiong-Hui Chen, Weinan Zhang, Yang Yu
  SCIENCE CHINA Information Sciences, 2023

2022

• Understanding Adversarial Imitation Learning in Small Sample Regime: A Stage-coupled Analysis
  Tian Xu*, Ziniu Li*, Yang Yu, Zhi-Quan Luo
  Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence
  (The early version of this work is at arXiv:2106.10424v3, titled On Generalization of Adversarial Imitation Learning and Beyond)

• Rethinking ValueDice: Does It Really Improve Performance?
  Ziniu Li*, Tian Xu*, Yang Yu, Zhi-Quan Luo
  In Proceedings of the 10th International Conference on Learning Representations (ICLR) (Blog Track), 2022
  

• A Note on Target Q-learning for Solving Finite MDPs with A Generative Oracle
  Ziniu Li*, Tian Xu*, Yang Yu
  Submitted to Artificial Intelligence

• Reinforcement Learning With Sparse-Executing Actions via Sparsity Regularization
  Jing-Cheng Pang, Tian Xu, Shengyi Jiang, Yu-Ren Liu, Yang Yu
  Submitted to IEEE Transactions on Neural Networks and Learning Systems

2021

• More Efficient Adversarial Imitation Learning Algorithms With Known and Unknown Transitions
  Tian Xu*, Ziniu Li*, Yang Yu
  Ecological Theory of RL Workshop in NeurIPS 2021.

• A Concise Introduction to Imitation Learning (In Chinese)
  Tian Xu, Ziniu Li, Yang Yu
  

• Error Bounds of Imitating Policies and Environments for Reinforcement Learning
  Tian Xu, Ziniu Li, Yang Yu
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021

2020

• Error Bounds of Imitating Policies and Environments
  Tian Xu, Ziniu Li, Yang Yu
  In Advances in Neural Information Processing Systems 33 (NeurIPS), 2020.

2019

• On Value Discrepancy of Imitation Learning
  Tian Xu, Ziniu Li, Yang Yu
  arXiv:1911.07027