Biography
I am currently a Ph.D. student supervised by Martin Müller and Dale Schuurmans.
I am also a student research in Google Brain.
My research interest is in the area of artificial intelligence and reinforcement learning. I am particularly interested in sequential decision making in complex problems.
Publication
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Escaping the Gravitational Pull of Softmax.
Jincheng Mei, Chenjun Xiao, Bo Dai, Lihong Li, Csaba Szepesvári, and Dale Schuurmans.
Advances in Neural Information Processing Systems (NeurIPS), Oral Presentation, 2020.
[arXiv (to appear)]
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On the Global Convergence Rates of Softmax Policy Gradient Methods.
Jincheng Mei, Chenjun Xiao, Csaba Szepesvári, and Dale Schuurmans.
International Conference on Machine Learning (ICML), 2020.
[arXiv]
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Learning to Combat Compounding-Error in Model-Based Reinforcement Learning.
Chenjun Xiao, Yifan Wu, Chen Ma, Dale Schuurmans, Martin Mueller.
NeurIPS 2019 Deep Reinforcement Learning Workshop.
[Paper]
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Maximum Entropy Monte-Carlo Planning.
Chenjun Xiao, Jincheng Mei, Ruitong Huang, Dale Schuurmans, Martin Müller.
Advances in Neural Information Processing Systems (NeurIPS), 2019.
[Paper][Poster]
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On Principled Entropy Exploration in Policy Optimization.
Jincheng Mei, Chenjun Xiao, Ruitong Huang, Dale Schuurmans, Martin Müller.
International Joint Conference on Artificial Intelligence (IJCAI), 2019.
[Paper][Long version]
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Memory-Augmented Monte Carlo Tree Search,
Chenjun Xiao, Jincheng Mei, Martin Müller.
AAAI Conference on Artificial Intelligence (AAAI), 2018.
Outstanding Paper Award
[Paper]
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Factorization Ranking Model for Move Prediction in the Game of Go,
Chenjun Xiao and Martin Müller.
AAAI Conference on Artificial Intelligence (AAAI), 2016.
[Paper]
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Only-One-Victor Pattern Learning in Computer Go,
Jiao Wang, Chenjun Xiao, Tan Zhu, Chu-Husan Hsueh, Wen-Jie Tseng and I-Chen Wu.
IEEE Transactions on Computational Intelligence and AI in Games, 2017.
[Paper]
Other Links
Last Modified: 2020-11-05