Chenjun Xiao

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 33

Top Topics

Temporal Difference

Policy Gradient Methods

Reinforcement Learning

Monte Carlo Tree Search

Top Venues

Publications

Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi, Oscar A Ramirez, Christopher K. Harris, A. Rupam Mahmood, Dale Schuurmans
Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation. CoRR (2024)
Dmitry Shribak, Chen-Xiao Gao, Yitong Li, Chenjun Xiao, Bo Dai
Diffusion Spectral Representation for Reinforcement Learning. CoRR (2024)
Yangchen Pan, Junfeng Wen, Chenjun Xiao, Philip H. S. Torr
An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models. CoRR (2024)
Xiaotian Hao, Jianye Hao, Chenjun Xiao, Kai Li, Dong Li, Yan Zheng
Multiagent Gumbel MuZero: Efficient Planning in Combinatorial Action Spaces. AAAI (2024)
Chen-Xiao Gao, Shengjun Fang, Chenjun Xiao, Yang Yu, Zongzhang Zhang
Hindsight Preference Learning for Offline Preference-based Reinforcement Learning. CoRR (2024)
Tianjun Zhang, Tongzheng Ren, Chenjun Xiao, Wenli Xiao, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai
Energy-based Predictive Representations for Partially Observed Reinforcement Learning. UAI (2023)
Xiaohan Hu, Yi Ma, Chenjun Xiao, Yan Zheng, Zhaopeng Meng
In-Sample Policy Iteration for Offline Reinforcement Learning. CoRR (2023)
Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran
Conditionally optimistic exploration for cooperative deep multi-agent reinforcement learning. UAI (2023)
Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai
Latent Variable Representation for Reinforcement Learning. ICLR (2023)
Chenjun Xiao, Han Wang, Yangchen Pan, Adam White, Martha White
The In-Sample Softmax for Offline Reinforcement Learning. ICLR (2023)
Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran
Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning. CoRR (2023)
Hongming Zhang, Chenjun Xiao, Han Wang, Jun Jin, Bo Xu, Martin Müller
Replay Memory as An Empirical MDP: Combining Conservative Estimation with Experience Replay. ICLR (2023)
Yi Ma, Chenjun Xiao, Hebin Liang, Jianye Hao
Rethinking Decision Transformer via Hierarchical Reinforcement Learning. CoRR (2023)
Chenjun Xiao, Han Wang, Yangchen Pan, Adam White, Martha White
The In-Sample Softmax for Offline Reinforcement Learning. CoRR (2023)
Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai
Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning. CoRR (2023)
Chenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvári
The Curse of Passive Data Collection in Batch Reinforcement Learning. AISTATS (2022)
Chenjun Xiao, Bo Dai, Jincheng Mei, Oscar A Ramirez, Ramki Gummadi, Chris Harris, Dale Schuurmans
Understanding and Leveraging Overparameterization in Recursive Value Estimation. ICLR (2022)
Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai
Latent Variable Representation for Reinforcement Learning. CoRR (2022)
Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvári, Dale Schuurmans
On the Optimality of Batch Policy Optimization Algorithms. ICML (2021)
Jincheng Mei, Bo Dai, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans
Understanding the Effect of Stochasticity in Policy Optimization. CoRR (2021)
Chenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvári
On the Sample Complexity of Batch Reinforcement Learning with Policy-Induced Data. CoRR (2021)
Chenjun Xiao, Yifan Wu, Tor Lattimore, Bo Dai, Jincheng Mei, Lihong Li, Csaba Szepesvári, Dale Schuurmans
On the Optimality of Batch Policy Optimization Algorithms. CoRR (2021)
Jincheng Mei, Bo Dai, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans
Understanding the Effect of Stochasticity in Policy Optimization. NeurIPS (2021)
Jincheng Mei, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans
On the Global Convergence Rates of Softmax Policy Gradient Methods. CoRR (2020)
Jincheng Mei, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans
On the Global Convergence Rates of Softmax Policy Gradient Methods. ICML (2020)
Jincheng Mei, Chenjun Xiao, Bo Dai, Lihong Li, Csaba Szepesvári, Dale Schuurmans
Escaping the Gravitational Pull of Softmax. NeurIPS (2020)
Jincheng Mei, Chenjun Xiao, Ruitong Huang, Dale Schuurmans, Martin Müller
On Principled Entropy Exploration in Policy Optimization. IJCAI (2019)
Chenjun Xiao, Yifan Wu, Chen Ma, Dale Schuurmans, Martin Müller
Learning to Combat Compounding-Error in Model-Based Reinforcement Learning. CoRR (2019)
Chenjun Xiao, Ruitong Huang, Jincheng Mei, Dale Schuurmans, Martin Müller
Maximum Entropy Monte-Carlo Planning. NeurIPS (2019)
Chenjun Xiao, Jincheng Mei, Martin Müller
Memory-Augmented Monte Carlo Tree Search. AAAI (2018)
Jiao Wang, Chenjun Xiao, Tan Zhu, Chu-Hsuan Hsueh, Wen-Jie Tseng, I-Chen Wu
Only-One-Victor Pattern Learning in Computer Go. IEEE Trans. Comput. Intell. AI Games 9 (1) (2017)
Chenjun Xiao, Martin Müller
Factorization Ranking Model for Move Prediction in the Game of Go. AAAI (2016)
Chenjun Xiao, Martin Müller
Integrating Factorization Ranked Features in MCTS: An Experimental Study. CGW@IJCAI (2016)
Jiao Wang, Hongye Li, Chenjun Xiao, Xin-He Xu
National University Student Computer-Games Tournaments. J. Int. Comput. Games Assoc. 35 (3) (2012)