• Publications
  
• Service
  
• Curriculum Vitae
  

Contact:

baichenjia255 (at) gmail.com
chenjia.bai (at) mail.utoronto.ca

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Chenjia Bai

Hi, this is Chenjia Bai (白辰甲). I'm a Ph.D. student in Computer Science at Harbin Institute of Technology (HIT), advised by Prof. Peng Liu. Currently, I am a visiting student at University of Toronto, working with Prof. Animesh Garg . My research mainly focuses on deep Reinforcement Learning (RL), including offline RL, efficient exploration, risk-sensitive learning, and multi-goal RL.

Before that, I was a visiting student at Northwestern University (remotely), working with Prof. Zhaoran Wang . I also used to be an intern at Huawei Noah's Ark Lab (advised by Prof. Jianye Hao), Tencent Robotics X (advised by Dr. Lei han), and Alibaba. I received my Bachelor's degree and Master's degree in Computer Science from HIT.

Publications

• xxx for Offline Reinforcement Learning. [arxiv]
  Chenjia Bai, et al.
  under review

• Exploration in Deep Reinforcement Learning: A Comprehensive Survey. [arxiv]
  Tianpei Yang*, Hongyao Tang*, Chenjia Bai*, Jinyi Liu*, Jianye Hao, Zhaopeng Meng, and Peng Liu (*Equally Contribution)
  under review

• Dynamic Bottleneck for Robust Self-Supervised Exploration. [arxiv, code]
  Chenjia Bai, Lingxiao Wang, Lei Han, Animesh Garg, Jianye Hao, Peng Liu, and Zhaoran Wang
  Neural Information Processing Systems (NeurIPS), 2021

• Principled Exploration via Optimistic Bootstrapping and Backward Induction . [pdf, arxiv, code]
  Chenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg, Peng Liu, and Zhaoran Wang
  International Conference on Machine Learning (ICML), 2021

• Addressing Hindsight Bias in Multi-Goal Reinforcement Learning. [pdf, code]
  Chenjia Bai, Lingxiao Wang, Yixin Wang, Zhaoran Wang, Rui Zhao, Chenyao Bai and Peng Liu
  IEEE Transactions on Cybernetics, 2021

• Variational Dynamic for Self-Supervised Exploration in Deep Reinforcement Learning. [arxiv, website]
  Chenjia Bai, Peng Liu, Zhaoran Wang, Kaiyu Liu, Lingxiao Wang, Yingnan Zhao, and Lei Han
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021 (2nd round).

• Generating Attentive Goals for Prioritized Hindsight Reinforcement Learning. [pdf]
  Peng Liu, Chenjia Bai, Yingnan Zhao, Chenyao Bai, Wei Zhao, and Xianglong Tang (supervisor first-author)
  Knowledge-Based Systems (KBS), 2020

• Obtaining Accurate Estimated Action Values in Categorical Distributional Reinforcement Learning. [pdf]
  Yingnan Zhao, Peng Liu, Chenjia Bai, Wei Zhao, and Xianglong Tang
  Knowledge-Based Systems (KBS), 2020

• Guided Goal Generation for Hindsight Multi-goal Reinforcement Learning. [pdf]
  Chenjia Bai, Peng Liu, Wei Zhao, and Xianglong Tang
  Neurocomputing, 2019

• Active Sampling for Deep Q-learning Based on TD-error Adaptive Correction. [pdf]
  Chenjia Bai, Peng Liu, Wei Zhao, and Xianglong Tang
  Journal of Computer Research and Development (in Chinese), 2019.

Service

• Conference Reviewer/Program Committee: AAAI (2021, 2022), NeurIPS (2021), ICLR (2021, 2022)

© 2021 Chenjia Bai