Yangchen Pan

According to our database, Yangchen Pan authored at least 32 papers between 2016 and 2024.

Collaborative distances:

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

2024

Label Alignment Regularization for Distribution Shift.

Ehsan Imani, Guojun Zhang, Runjia Li, Jun Luo, Pascal Poupart, Philip H. S. Torr, Yangchen Pan

J. Mach. Learn. Res., 2024

DTR-Bench: An in silico Environment and Benchmark Platform for Reinforcement Learning Based Dynamic Treatment Regime.

Zhiyao Luo, Mingcheng Zhu, Fenglin Liu, Jiali Li, Yangchen Pan, Jiandong Zhou, Tingting Zhu

CoRR, 2024

Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination.

Zhiyao Luo, Yangchen Pan, Peter J. Watkinson, Tingting Zhu

CoRR, 2024

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

Yangchen Pan, Junfeng Wen, Chenjun Xiao, Philip Torr

CoRR, 2024

A Simple Mixture Policy Parameterization for Improving Sample Efficiency of CVaR Optimization.

Yudong Luo, Yangchen Pan, Han Wang, Philip Torr, Pascal Poupart

RLJ, 2024

Position: Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination.

Zhiyao Luo, Yangchen Pan, Peter J. Watkinson, Tingting Zhu

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

Improving Adversarial Transferability via Model Alignment.

Avery Ma, Amir-massoud Farahmand, Yangchen Pan, Philip Torr, Jindong Gu

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods.

Avery Ma, Yangchen Pan, Amir-massoud Farahmand

Trans. Mach. Learn. Res., 2023

Memory-efficient Reinforcement Learning with Value-based Knowledge Consolidation.

Qingfeng Lan, Yangchen Pan, Jun Luo, A. Rupam Mahmood

Trans. Mach. Learn. Res., 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

An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient.

Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement.

Samuel Neumann, Sungsu Lim, Ajin George Joseph, Yangchen Pan, Adam White, Martha White

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Label Alignment Regularization for Distribution Shift.

Ehsan Imani, Guojun Zhang, Jun Luo, Pascal Poupart, Yangchen Pan

CoRR, 2022

Memory-efficient Reinforcement Learning with Knowledge Consolidation.

Qingfeng Lan, Yangchen Pan, Jun Luo, A. Rupam Mahmood

CoRR, 2022

Understanding and mitigating the limitations of prioritized experience replay.

Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand, Martha White, Hengshuai Yao, Mohsen Rohani, Jun Luo

Proceedings of the Uncertainty in Artificial Intelligence, 2022

TOPS: Transition-Based Volatility-Reduced Policy Search.

Liangliang Xu, Daoming Lyu, Yangchen Pan, Aiwen Jiang, Bo Liu

Proceedings of the Autonomous Agents and Multiagent Systems. Best and Visionary Papers, 2022

An Alternate Policy Gradient Estimator for Softmax Policies.

Shivam Garg, Samuele Tosatto, Yangchen Pan, Martha White, Rupam Mahmood

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

2021

Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online.

Yangchen Pan, Kirby Banman, Martha White

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Beyond Prioritized Replay: Sampling States in Model-Based RL via Simulated Priorities.

Jincheng Mei, Yangchen Pan, Martha White, Amir-massoud Farahmand, Hengshuai Yao

CoRR, 2020

An implicit function learning approach for parametric modal regression.

Yangchen Pan, Ehsan Imani, Amir-massoud Farahmand, Martha White

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

Frequency-based Search-control in Dyna.

Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand

Proceedings of the 8th International Conference on Learning Representations, 2020

Maxmin Q-learning: Controlling the Estimation Bias of Q-learning.

Qingfeng Lan, Yangchen Pan, Alona Fyshe, Martha White

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Deep Tile Coder: an Efficient Sparse Representation Learning Approach with applications in Reinforcement Learning.

Yangchen Pan

CoRR, 2019

Hill Climbing on Value Estimates for Search-control in Dyna.

Yangchen Pan, Hengshuai Yao, Amir-massoud Farahmand, Martha White

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

2018

Actor-Expert: A Framework for using Action-Value Methods in Continuous Action Spaces.

Sungsu Lim, Ajin Joseph, Lei Le, Yangchen Pan, Martha White

CoRR, 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

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

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

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Effective sketching methods for value function approximation.

Yangchen Pan, Erfan Sadeqi Azer, Martha White

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Adapting Kernel Representations Online Using Submodular Maximization.

Matthew Schlegel, Yangchen Pan, Jiecao Chen, Martha White

Proceedings of the 34th International Conference on Machine Learning, 2017

Accelerated Gradient Temporal Difference Learning.

Yangchen Pan, Adam White, Martha White

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Incremental Truncated LSTD.

Clement Gehring, Yangchen Pan, Martha White

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016