Chenjun Xiao

According to our database, Chenjun Xiao authored at least 29 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Hindsight Preference Learning for Offline Preference-based Reinforcement Learning.

Chen-Xiao Gao, Shengjun Fang, Chenjun Xiao, Yang Yu, Zongzhang Zhang

CoRR, 2024

Diffusion Spectral Representation for Reinforcement Learning.

Dmitry Shribak, Chen-Xiao Gao, Yitong Li, Chenjun Xiao, Bo Dai

CoRR, 2024

An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models.

Yangchen Pan, Junfeng Wen, Chenjun Xiao, Philip Torr

CoRR, 2024

Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning.

Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Rethinking Decision Transformer via Hierarchical Reinforcement Learning.

Yi Ma, Jianye Hao, Hebin Liang, Chenjun Xiao

Proceedings of the Forty-first International Conference on Machine Learning, 2024

HarmonyDream: Task Harmonization Inside World Models.

Haoyu Ma, Jialong Wu, Ningya Feng, Chenjun Xiao, Dong Li, Jianye Hao, Jianmin Wang, Mingsheng Long

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation.

Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi, Oscar A. Ramirez, Christopher K. Harris, A. Rupam Mahmood, Dale Schuurmans

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Multiagent Gumbel MuZero: Efficient Planning in Combinatorial Action Spaces.

Xiaotian Hao, Jianye Hao, Chenjun Xiao, Kai Li, Dong Li, Yan Zheng

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

In-Sample Policy Iteration for Offline Reinforcement Learning.

Xiaohan Hu, Yi Ma, Chenjun Xiao, Yan Zheng, Zhaopeng Meng

CoRR, 2023

Conditionally optimistic exploration for cooperative deep multi-agent reinforcement learning.

Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Energy-based Predictive Representations for Partially Observed Reinforcement Learning.

Tianjun Zhang, Tongzheng Ren, Chenjun Xiao, Wenli Xiao, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Replay Memory as An Empirical MDP: Combining Conservative Estimation with Experience Replay.

Hongming Zhang, Chenjun Xiao, Han Wang, Jun Jin, Bo Xu, Martin Müller

Proceedings of the Eleventh International Conference on Learning Representations, 2023

The In-Sample Softmax for Offline Reinforcement Learning.

Chenjun Xiao, Han Wang, Yangchen Pan, Adam White, Martha White

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Latent Variable Representation for Reinforcement Learning.

Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Understanding and Leveraging Overparameterization in Recursive Value Estimation.

Chenjun Xiao, Bo Dai, Jincheng Mei, Oscar A. Ramirez, Ramki Gummadi, Chris Harris, Dale Schuurmans

Proceedings of the Tenth International Conference on Learning Representations, 2022

The Curse of Passive Data Collection in Batch Reinforcement Learning.

Chenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvári

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

On the Sample Complexity of Batch Reinforcement Learning with Policy-Induced Data.

Chenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvári

CoRR, 2021

Understanding the Effect of Stochasticity in Policy Optimization.

Jincheng Mei, Bo Dai, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the Optimality of Batch Policy Optimization Algorithms.

Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvári, Dale Schuurmans

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Escaping the Gravitational Pull of Softmax.

Jincheng Mei, Chenjun Xiao, Bo Dai, Lihong Li, Csaba Szepesvári, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On the Global Convergence Rates of Softmax Policy Gradient Methods.

Jincheng Mei, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Learning to Combat Compounding-Error in Model-Based Reinforcement Learning.

Chenjun Xiao, Yifan Wu, Chen Ma, Dale Schuurmans, Martin Müller

CoRR, 2019

Maximum Entropy Monte-Carlo Planning.

Chenjun Xiao, Ruitong Huang, Jincheng Mei, Dale Schuurmans, Martin Müller

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On Principled Entropy Exploration in Policy Optimization.

Jincheng Mei, Chenjun Xiao, Ruitong Huang, Dale Schuurmans, Martin Müller

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

Memory-Augmented Monte Carlo Tree Search.

Chenjun Xiao, Jincheng Mei, Martin Müller

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Only-One-Victor Pattern Learning in Computer Go.

Jiao Wang, Chenjun Xiao, Tan Zhu, Chu-Hsuan Hsueh, Wen-Jie Tseng, I-Chen Wu

IEEE Trans. Comput. Intell. AI Games, 2017

2016

Integrating Factorization Ranked Features in MCTS: An Experimental Study.

Chenjun Xiao, Martin Müller

Proceedings of the Computer Games - 5th Workshop on Computer Games, 2016

Factorization Ranking Model for Move Prediction in the Game of Go.

Chenjun Xiao, Martin Müller

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2012

The 2^nd National University Student Computer-Games Tournaments.

Jiao Wang, Hongye Li, Chenjun Xiao, Xin-He Xu

J. Int. Comput. Games Assoc., 2012