I am Yangchen Pan (Google Scholar), a PhD student in the Department of Computing Science, University of Alberta. My PhD advisors are Dr. Martha White (University of Alberta) and Dr. Amir-massoud Farahmand (University of Toronto & Vector Institute). I am broadly interested in machine learning and reinforcement learning. My most recent work includes model-based reinforcement learning, representation learning, parametric modal regression.
Referred Conference Publications
An implicit function learning approach for parametric modal regression. Yangchen Pan, Ehsan Imani, Martha White, Amir-massoud Farahmand. Conference on Neural Information Processing Systems (NeurIPS), 2020.
Maxmin Q-learning: Controlling the Estimation Bias of Q-learning. Qingfeng Lan, Yangchen Pan, Alona Fyshe, Martha White. International Conference on Learning Representations (ICLR), 2020.
Frequency-based Search-control in Dyna. Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand. International Conference on Learning Representations (ICLR), 2020.
Hill Climbing on Value Estimates for Search-control in Dyna. Yangchen Pan, Hengshuai Yao, Amir-massoud Farahmand, Martha White. International Joint Conference on Artificial Intelligence (IJCAI), 2019.
Reinforcement learning with function-valued action spaces for partial differential equation control. Yangchen Pan, Amir-massoud Farahmand, Martha White, Saleh Nabi, Piyush Grover, Daniel Nikovski. International Conference on Machine Learning (ICML), 2018.
Organizing experience: a deeper look at replay mechanisms for sample-based planning in continuous state domains. Yangchen Pan, Muhammad Zaheer, Adam White, Andrew Patterson, Martha White. International Joint Conference on Artificial Intelligence (IJCAI), 2018.
Adapting kernel representations online using submodular maximization. Matthew Schlegel, Yangchen Pan, Jiecao Chen, Martha White. International Conference on Machine Learning (ICML), 2017.
Effective sketching methods for value function approximation. Yangchen Pan, Erfan Sadeqi Azer, Martha White. Conference on Uncertainty in Artificial Intelligence (UAI), 2017.
Accelerated gradient temporal difference learning. Yangchen Pan, Adam White, Martha White. AAAI Conference on Artificial Intelligence (AAAI), 2017.
Incremental truncated LSTD. Clement Gehring, Yangchen Pan, Martha White. International Joint Conference on Artificial Intelligence (IJCAI), 2016.
Preprints/Workshop/Work in progress
Beyond Prioritized Replay: Sampling States in Model-Based RL via Simulated Priorities. Jincheng Mei, Yangchen Pan (co-first author), Amir-massoud Farahmand, Martha White, Hengshuai Yao. Under Review. 2020.
Leaky Tiling Activations: A Simple Approach to Learning Sparse Representations Online. Yangchen Pan, Kirby Banman, White Martha. Under Review. 2020.
Actor-expert: A framework for using action-value methods in continuous action spaces. Sungsu Lim, Ajin Joseph, Lei Le, Yangchen Pan, Martha White. 2020.
Accelerated Gradient Temporal Difference Learning. European workshop on reinforcement learning (EWRL), 2017.
Conference Program Committee Member, Reviewer
NeurIPS 2018, ICML 2019, AAAI 2019, ICLR 2020, NeurIPS 2020, AAAI 2020, AAAI 2021, ICLR 2021, AISTATS 2021.
AAAI 2017, ICLR 2017, AAAI 2018, AAMAS 2018, ICML 2018, ICLR 2019, NeurIPS 2020
Journal of Machine Learning Research (JMLR) 2020, one paper
2019 Fall: CMPUT 466/566, Machine Learning, Teaching Assistant, University of Alberta
2019 Spring: CMPUT 272, Formal Systems and Logic in Computing Science, Teaching Assistant, University of Alberta
2016 Spring: CSCI C343, Data Structure, Associate Instructor, Indiana University at Bloomington
2015 Fall: CSCI B503, Algorithm Design and Analysis, Associate Instructor, Indiana University at Bloomington
2014 Fall: CSCI 1311 Discrete Structure I, Teaching Assistant, George Washington University
Research Intern at Huawei Technologies, Edmonton, AB, Canada, 05/2018-12/2018
Research Intern at Mitsubishi Electric Research Laboratories, Boston, MA, the United States, 05/2017-08/2017