Chenjun Xiao - RankMe

50 papers A* 22A 4Journal 23Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models (Abstract Reprint). AAAI Yangchen Pan, Junfeng Wen, Chenjun Xiao, Philip Torr
2025	J	`jnl`	An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models. J. Artif. Intell. Res. Yangchen Pan, Junfeng Wen, Chenjun Xiao, Philip H. S. Torr
2025	A*	`conf`	Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning. ICML Chen-Xiao Gao, Chenyang Wu, Mingjun Cao, Chenjun Xiao, Yang Yu, Zongzhang Zhang
2025	J	`jnl`	Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning. CoRR Chen-Xiao Gao, Chenyang Wu, Mingjun Cao, Chenjun Xiao, Yang Yu, Zongzhang Zhang
2025	J	`jnl`	Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning. CoRR Haiming Wang, Mert Unsal, Xiaohan Lin, Mantas Baksys, Junqi Liu, Marco Dos Santos, Flood Sung, Marina Vinyes, Zhenzhe Ying, Zekai Zhu, Jianqiao Lu, Hugues de Saxcé, Bolton Bailey, Chendong Song, Chenjun Xiao, Dehao Zhang, Ebony Zhang, Frederick Pu, Han Zhu, Jiawei Liu, Jonas Bayer, Julien Michel, Longhui Yu, Léo Dreyfus-Schmidt, Lewis Tunstall, Luigi Pagani, Moreira Machado, Pauline Bourigault, Ran Wang, Stanislas Polu, Thibaut Barroyer, Wen-Ding Li, Yazhe Niu, Yann Fleureau, Yangyang Hu, Zhouliang Yu, Zihan Wang, Zhilin Yang, Zhengying Liu, Jia Li
2025	J	`jnl`	Large Language Model-Enhanced Multi-Armed Bandits. CoRR Jiahang Sun, Zhiyong Wang, Runhan Yang, Chenjun Xiao, John C. S. Lui, Zhongxiang Dai
2025	J	`jnl`	Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies. CoRR Yi Ma, Hongyao Tang, Chenjun Xiao, Yaodong Yang, Wei Wei, Jianye Hao, Jiye Liang
2025	A	`conf`	β-DQN: Improving Deep Q-Learning By Evolving the Behavior. AAMAS Hongming Zhang, Fengshuo Bai, Chenjun Xiao, Chao Gao, Bo Xu, Martin Müller
2025	J	`jnl`	β-DQN: Improving Deep Q-Learning By Evolving the Behavior. CoRR Hongming Zhang, Fengshuo Bai, Chenjun Xiao, Chao Gao, Bo Xu, Martin Müller
2024	J	`jnl`	An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models. CoRR Yangchen Pan, Junfeng Wen, Chenjun Xiao, Philip Torr
2024	A*	`conf`	Diffusion Spectral Representation for Reinforcement Learning. NeurIPS Dmitry Shribak, Chen-Xiao Gao, Yitong Li, Chenjun Xiao, Bo Dai
2024	J	`jnl`	Diffusion Spectral Representation for Reinforcement Learning. CoRR Dmitry Shribak, Chen-Xiao Gao, Yitong Li, Chenjun Xiao, Bo Dai
2024	A*	`conf`	Exploiting the Replay Memory Before Exploring the Environment: Enhancing Reinforcement Learning Through Empirical MDP Iteration. NeurIPS Hongming Zhang, Chenjun Xiao, Chao Gao, Han Wang, Bo Xu, Martin Müller
2024	A*	`conf`	HarmonyDream: Task Harmonization Inside World Models. ICML Haoyu Ma, Jialong Wu, Ningya Feng, Chenjun Xiao, Dong Li, Jianye Hao, Jianmin Wang, Mingsheng Long
2024	J	`jnl`	Hindsight Preference Learning for Offline Preference-based Reinforcement Learning. CoRR Chen-Xiao Gao, Shengjun Fang, Chenjun Xiao, Yang Yu, Zongzhang Zhang
2024	A*	`conf`	Iteratively Refined Behavior Regularization for Offline Reinforcement Learning. NeurIPS Yi Ma, Jianye Hao, Xiaohan Hu, Yan Zheng, Chenjun Xiao
2024	A*	`conf`	Multiagent Gumbel MuZero: Efficient Planning in Combinatorial Action Spaces. AAAI Xiaotian Hao, Jianye Hao, Chenjun Xiao, Kai Li, Dong Li, Yan Zheng
2024	A*	`conf`	Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning. ICML Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai
2024	A*	`conf`	Rethinking Decision Transformer via Hierarchical Reinforcement Learning. ICML Yi Ma, Jianye Hao, Hebin Liang, Chenjun Xiao
2024	A*	`conf`	Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation. ICML Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi, Oscar A. Ramirez, Christopher K. Harris, A. Rupam Mahmood, Dale Schuurmans
2024	J	`jnl`	Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation. CoRR Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi, Oscar A. Ramirez, Christopher K. Harris, A. Rupam Mahmood, Dale Schuurmans
2023	J	`jnl`	Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning. CoRR Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran
2023	A	`conf`	Conditionally optimistic exploration for cooperative deep multi-agent reinforcement learning. UAI Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran
2023	A	`conf`	Energy-based Predictive Representations for Partially Observed Reinforcement Learning. UAI Tianjun Zhang, Tongzheng Ren, Chenjun Xiao, Wenli Xiao, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai
2023	J	`jnl`	In-Sample Policy Iteration for Offline Reinforcement Learning. CoRR Xiaohan Hu, Yi Ma, Chenjun Xiao, Yan Zheng, Zhaopeng Meng
2023	A*	`conf`	Latent Variable Representation for Reinforcement Learning. ICLR Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai
2023	J	`jnl`	Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning. CoRR Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai
2023	A*	`conf`	Replay Memory as An Empirical MDP: Combining Conservative Estimation with Experience Replay. ICLR Hongming Zhang, Chenjun Xiao, Han Wang, Jun Jin, Bo Xu, Martin Müller
2023	J	`jnl`	Rethinking Decision Transformer via Hierarchical Reinforcement Learning. CoRR Yi Ma, Chenjun Xiao, Hebin Liang, Jianye Hao
2023	A*	`conf`	The In-Sample Softmax for Offline Reinforcement Learning. ICLR Chenjun Xiao, Han Wang, Yangchen Pan, Adam White, Martha White
2023	J	`jnl`	The In-Sample Softmax for Offline Reinforcement Learning. CoRR Chenjun Xiao, Han Wang, Yangchen Pan, Adam White, Martha White
2022	J	`jnl`	Latent Variable Representation for Reinforcement Learning. CoRR Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai
2022	A	`conf`	The Curse of Passive Data Collection in Batch Reinforcement Learning. AISTATS Chenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvári
2022	A*	`conf`	Understanding and Leveraging Overparameterization in Recursive Value Estimation. ICLR Chenjun Xiao, Bo Dai, Jincheng Mei, Oscar A. Ramirez, Ramki Gummadi, Chris Harris, Dale Schuurmans
2021	A*	`conf`	On the Optimality of Batch Policy Optimization Algorithms. ICML Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvári, Dale Schuurmans
2021	J	`jnl`	On the Optimality of Batch Policy Optimization Algorithms. CoRR Chenjun Xiao, Yifan Wu, Tor Lattimore, Bo Dai, Jincheng Mei, Lihong Li, Csaba Szepesvári, Dale Schuurmans
2021	J	`jnl`	On the Sample Complexity of Batch Reinforcement Learning with Policy-Induced Data. CoRR Chenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvári
2021	A*	`conf`	Understanding the Effect of Stochasticity in Policy Optimization. NeurIPS Jincheng Mei, Bo Dai, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans
2021	J	`jnl`	Understanding the Effect of Stochasticity in Policy Optimization. CoRR Jincheng Mei, Bo Dai, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans
2020	A*	`conf`	Escaping the Gravitational Pull of Softmax. NeurIPS Jincheng Mei, Chenjun Xiao, Bo Dai, Lihong Li, Csaba Szepesvári, Dale Schuurmans
2020	A*	`conf`	On the Global Convergence Rates of Softmax Policy Gradient Methods. ICML Jincheng Mei, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans
2020	J	`jnl`	On the Global Convergence Rates of Softmax Policy Gradient Methods. CoRR Jincheng Mei, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans
2019	J	`jnl`	Learning to Combat Compounding-Error in Model-Based Reinforcement Learning. CoRR Chenjun Xiao, Yifan Wu, Chen Ma, Dale Schuurmans, Martin Müller
2019	A*	`conf`	Maximum Entropy Monte-Carlo Planning. NeurIPS Chenjun Xiao, Ruitong Huang, Jincheng Mei, Dale Schuurmans, Martin Müller
2019	A*	`conf`	On Principled Entropy Exploration in Policy Optimization. IJCAI Jincheng Mei, Chenjun Xiao, Ruitong Huang, Dale Schuurmans, Martin Müller
2018	A*	`conf`	Memory-Augmented Monte Carlo Tree Search. AAAI Chenjun Xiao, Jincheng Mei, Martin Müller
2017	J	`jnl`	Only-One-Victor Pattern Learning in Computer Go. IEEE Trans. Comput. Intell. AI Games Jiao Wang, Chenjun Xiao, Tan Zhu, Chu-Hsuan Hsueh, Wen-Jie Tseng, I-Chen Wu
2016	A*	`conf`	Factorization Ranking Model for Move Prediction in the Game of Go. AAAI Chenjun Xiao, Martin Müller
2016	—	`conf`	Integrating Factorization Ranked Features in MCTS: An Experimental Study. CGW@IJCAI Chenjun Xiao, Martin Müller
2012	J	`jnl`	The 2 ICGA J. Jiao Wang, Hongye Li, Chenjun Xiao, Xin-He Xu