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Journal Articles
- 2024
[j3]Ehsan Imani, Guojun Zhang, Runjia Li, Jun Luo, Pascal Poupart, Philip H. S. Torr, Yangchen Pan:
Label Alignment Regularization for Distribution Shift. J. Mach. Learn. Res. 25: 247:1-247:32 (2024)- 2023
- [j2]Qingfeng Lan, Yangchen Pan
, Jun Luo, A. Rupam Mahmood:
Memory-efficient Reinforcement Learning with Value-based Knowledge Consolidation. Trans. Mach. Learn. Res. 2023 (2023) - [j1]Avery Ma, Yangchen Pan, Amir-massoud Farahmand:
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods. Trans. Mach. Learn. Res. 2023 (2023)
Conference and Workshop Papers
- 2024
- [c19]Zhiyao Luo, Yangchen Pan, Peter J. Watkinson, Tingting Zhu:
Position: Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination. ICML 2024 - 2023
- [c18]Samuel Neumann, Sungsu Lim, Ajin George Joseph, Yangchen Pan, Adam White, Martha White:
Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement. ICLR 2023 - [c17]Chenjun Xiao, Han Wang, Yangchen Pan, Adam White, Martha White:
The In-Sample Softmax for Offline Reinforcement Learning. ICLR 2023 - [c16]Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan:
An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient. NeurIPS 2023 - [c15]Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran:
Conditionally optimistic exploration for cooperative deep multi-agent reinforcement learning. UAI 2023: 2529-2540 - 2022
- [c14]Shivam Garg, Samuele Tosatto, Yangchen Pan, Martha White, Rupam Mahmood:
An Alternate Policy Gradient Estimator for Softmax Policies. AISTATS 2022: 6630-6689 - [c13]Liangliang Xu, Daoming Lyu, Yangchen Pan, Aiwen Jiang, Bo Liu:
TOPS: Transition-Based Volatility-Reduced Policy Search. AAMAS Workshops 2022: 3-47 - [c12]Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand, Martha White, Hengshuai Yao, Mohsen Rohani, Jun Luo:
Understanding and mitigating the limitations of prioritized experience replay. UAI 2022: 1561-1571 - 2021
- [c11]Yangchen Pan, Kirby Banman, Martha White:
Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online. ICLR 2021 - 2020
- [c10]Qingfeng Lan, Yangchen Pan, Alona Fyshe, Martha White:
Maxmin Q-learning: Controlling the Estimation Bias of Q-learning. ICLR 2020 - [c9]Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand:
Frequency-based Search-control in Dyna. ICLR 2020 - [c8]Yangchen Pan, Ehsan Imani, Amir-massoud Farahmand, Martha White:
An implicit function learning approach for parametric modal regression. NeurIPS 2020 - 2019
- [c7]Yangchen Pan, Hengshuai Yao, Amir-massoud Farahmand, Martha White:
Hill Climbing on Value Estimates for Search-control in Dyna. IJCAI 2019: 3209-3215 - 2018
- [c6]Yangchen Pan, Amir-massoud Farahmand, Martha White, Saleh Nabi, Piyush Grover, Daniel Nikovski:
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control. ICML 2018: 3983-3992 - [c5]Yangchen Pan, Muhammad Zaheer, Adam White, Andrew Patterson, Martha White:
Organizing Experience: a Deeper Look at Replay Mechanisms for Sample-Based Planning in Continuous State Domains. IJCAI 2018: 4794-4800 - 2017
- [c4]Yangchen Pan, Adam White, Martha White:
Accelerated Gradient Temporal Difference Learning. AAAI 2017: 2464-2470 - [c3]Matthew Schlegel, Yangchen Pan, Jiecao Chen, Martha White:
Adapting Kernel Representations Online Using Submodular Maximization. ICML 2017: 3037-3046 - [c2]Yangchen Pan, Erfan Sadeqi Azer, Martha White:
Effective sketching methods for value function approximation. UAI 2017 - 2016
- [c1]Clement Gehring, Yangchen Pan, Martha White:
Incremental Truncated LSTD. IJCAI 2016: 1505-1511
Informal and Other Publications
- 2024
- [i23]Yudong Luo, Yangchen Pan, Han Wang, Philip Torr, Pascal Poupart:
A Simple Mixture Policy Parameterization for Improving Sample Efficiency of CVaR Optimization. CoRR abs/2403.11062 (2024) - [i22]Yangchen Pan, Junfeng Wen, Chenjun Xiao, Philip Torr:
An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models. CoRR abs/2404.15518 (2024) - [i21]Zhiyao Luo, Yangchen Pan, Peter J. Watkinson, Tingting Zhu:
Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination. CoRR abs/2405.18556 (2024) - [i20]Zhiyao Luo, Mingcheng Zhu, Fenglin Liu, Jiali Li, Yangchen Pan, Jiandong Zhou, Tingting Zhu:
DTR-Bench: An in silico Environment and Benchmark Platform for Reinforcement Learning Based Dynamic Treatment Regime. CoRR abs/2405.18610 (2024) - 2023
- [i19]Chenjun Xiao, Han Wang, Yangchen Pan, Adam White, Martha White:
The In-Sample Softmax for Offline Reinforcement Learning. CoRR abs/2302.14372 (2023) - [i18]Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran:
Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning. CoRR abs/2303.09032 (2023) - [i17]Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan:
An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient. CoRR abs/2307.08873 (2023) - [i16]Avery Ma, Yangchen Pan, Amir-massoud Farahmand:
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods. CoRR abs/2308.06703 (2023) - [i15]Avery Ma, Amir-massoud Farahmand, Yangchen Pan, Philip H. S. Torr, Jindong Gu:
Improving Adversarial Transferability via Model Alignment. CoRR abs/2311.18495 (2023) - 2022
- [i14]Qingfeng Lan, Yangchen Pan, Jun Luo, A. Rupam Mahmood:
Memory-efficient Reinforcement Learning with Knowledge Consolidation. CoRR abs/2205.10868 (2022) - [i13]Ehsan Imani, Guojun Zhang, Jun Luo, Pascal Poupart, Yangchen Pan:
Label Alignment Regularization for Distribution Shift. CoRR abs/2211.14960 (2022) - 2021
- [i12]Shivam Garg, Samuele Tosatto, Yangchen Pan, Martha White, A. Rupam Mahmood:
An Alternate Policy Gradient Estimator for Softmax Policies. CoRR abs/2112.11622 (2021) - 2020
- [i11]Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand:
Frequency-based Search-control in Dyna. CoRR abs/2002.05822 (2020) - [i10]Yangchen Pan, Ehsan Imani, Martha White, Amir-massoud Farahmand:
An implicit function learning approach for parametric modal regression. CoRR abs/2002.06195 (2020) - [i9]Qingfeng Lan, Yangchen Pan, Alona Fyshe, Martha White:
Maxmin Q-learning: Controlling the Estimation Bias of Q-learning. CoRR abs/2002.06487 (2020) - [i8]Jincheng Mei, Yangchen Pan, Martha White, Amir-massoud Farahmand, Hengshuai Yao:
Beyond Prioritized Replay: Sampling States in Model-Based RL via Simulated Priorities. CoRR abs/2007.09569 (2020) - 2019
- [i7]Yangchen Pan, Hengshuai Yao, Amir-massoud Farahmand, Martha White:
Hill Climbing on Value Estimates for Search-control in Dyna. CoRR abs/1906.07791 (2019) - [i6]Yangchen Pan:
Deep Tile Coder: an Efficient Sparse Representation Learning Approach with applications in Reinforcement Learning. CoRR abs/1911.08068 (2019) - 2018
- [i5]Yangchen Pan, Muhammad Zaheer, Adam White, Andrew Patterson, Martha White:
Organizing Experience: A Deeper Look at Replay Mechanisms for Sample-based Planning in Continuous State Domains. CoRR abs/1806.04624 (2018) - [i4]Yangchen Pan, Amir-massoud Farahmand, Martha White, Saleh Nabi, Piyush Grover, Daniel Nikovski:
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control. CoRR abs/1806.06931 (2018) - [i3]Sungsu Lim, Ajin Joseph, Lei Le, Yangchen Pan, Martha White:
Actor-Expert: A Framework for using Action-Value Methods in Continuous Action Spaces. CoRR abs/1810.09103 (2018) - 2017
- [i2]Yangchen Pan, Erfan Sadeqi Azer, Martha White:
Effective sketching methods for value function approximation. CoRR abs/1708.01298 (2017) - 2016
- [i1]Yangchen Pan, Adam White, Martha White:
Accelerated Gradient Temporal Difference Learning. CoRR abs/1611.09328 (2016)
Coauthor Index
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