Incremental Truncated LSTD. - Clement Gehring; Yangchen Pan; Martha White (IJCAI, 2016)

Accelerated Gradient Temporal Difference Learning. - Yangchen Pan; Adam White 001; Martha White (AAAI, 2017)

Adapting Kernel Representations Online Using Submodular Maximization. - Matthew Schlegel; Yangchen Pan; Jiecao Chen; Martha White (ICML, 2017)

Effective sketching methods for value function approximation. - Yangchen Pan; Erfan Sadeqi Azer; Martha White (UAI, 2017)

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 (ICML, 2018)

Organizing Experience: a Deeper Look at Replay Mechanisms for Sample-Based Planning in Continuous State Domains. - Yangchen Pan; Muhammad Zaheer; Adam White 001; Andrew Patterson; Martha White (IJCAI, 2018)

Actor-Expert: A Framework for using Action-Value Methods in Continuous Action Spaces. - Sungsu Lim; Ajin Joseph 001; Lei Le; Yangchen Pan; Martha White (CoRR, 2018)

Hill Climbing on Value Estimates for Search-control in Dyna. - Yangchen Pan; Hengshuai Yao; Amir-massoud Farahmand; Martha White (IJCAI, 2019)

Deep Tile Coder: an Efficient Sparse Representation Learning Approach with applications in Reinforcement Learning. - Yangchen Pan (CoRR, 2019)

Maxmin Q-learning: Controlling the Estimation Bias of Q-learning. - Qingfeng Lan; Yangchen Pan; Alona Fyshe; Martha White (ICLR, 2020)

Frequency-based Search-control in Dyna. - Yangchen Pan; Jincheng Mei; Amir-massoud Farahmand (ICLR, 2020)

An implicit function learning approach for parametric modal regression. - Yangchen Pan; Ehsan Imani; Amir-massoud Farahmand; Martha White (NeurIPS, 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)

Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online. - Yangchen Pan; Kirby Banman; Martha White (ICLR, 2021)

An Alternate Policy Gradient Estimator for Softmax Policies. - Shivam Garg 006; Samuele Tosatto; Yangchen Pan; Martha White; Rupam Mahmood (AISTATS, 2022)

TOPS: Transition-Based Volatility-Reduced Policy Search. - Liangliang Xu; Daoming Lyu; Yangchen Pan; Aiwen Jiang; Bo Liu 006 (AAMAS Workshops, 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 009 (UAI, 2022)

Memory-efficient Reinforcement Learning with Knowledge Consolidation. - Qingfeng Lan; Yangchen Pan; Jun Luo 009; A. Rupam Mahmood (CoRR, 2022)

Label Alignment Regularization for Distribution Shift. - Ehsan Imani; Guojun Zhang; Jun Luo 009; Pascal Poupart; Yangchen Pan (CoRR, 2022)

Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement. - Samuel Neumann; Sungsu Lim; Ajin George Joseph; Yangchen Pan; Adam White 001; Martha White (ICLR, 2023)

The In-Sample Softmax for Offline Reinforcement Learning. - Chenjun Xiao; Han Wang; Yangchen Pan; Adam White 001; Martha White (ICLR, 2023)

An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient. - Yudong Luo; Guiliang Liu; Pascal Poupart; Yangchen Pan (NeurIPS, 2023)

Conditionally optimistic exploration for cooperative deep multi-agent reinforcement learning. - Xutong Zhao; Yangchen Pan; Chenjun Xiao; Sarath Chandar; Janarthanan Rajendran (UAI, 2023)

Memory-efficient Reinforcement Learning with Value-based Knowledge Consolidation. - Qingfeng Lan; Yangchen Pan; Jun Luo 009; A. Rupam Mahmood (Trans. Mach. Learn. Res., 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)

Improving Adversarial Transferability via Model Alignment. - Avery Ma; Amir-massoud Farahmand; Yangchen Pan; Philip Torr 001; Jindong Gu (ECCV (62), 2024)

Position: Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination. - Zhiyao Luo; Yangchen Pan; Peter J. Watkinson; Tingting Zhu 001 (ICML, 2024)

A Simple Mixture Policy Parameterization for Improving Sample Efficiency of CVaR Optimization. - Yudong Luo; Yangchen Pan; Han Wang; Philip Torr 001; Pascal Poupart (RLJ, 2024)

Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination. - Zhiyao Luo; Yangchen Pan; Peter J. Watkinson; Tingting Zhu 001 (CoRR, 2024)

DTR-Bench: An in silico Environment and Benchmark Platform for Reinforcement Learning Based Dynamic Treatment Regime. - Zhiyao Luo; Mingcheng Zhu 001; Fenglin Liu; Jiali Li; Yangchen Pan; Jiandong Zhou 003; Tingting Zhu 001 (CoRR, 2024)

Label Alignment Regularization for Distribution Shift. - Ehsan Imani; Guojun Zhang; Runjia Li; Jun Luo 009; Pascal Poupart; Philip H. S. Torr; Yangchen Pan (J. Mach. Learn. Res., 2024)

An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models. - Yangchen Pan; Junfeng Wen; Chenjun Xiao; Philip H. S. Torr (J. Artif. Intell. Res., 2025)

PANDAS: Improving Many-shot Jailbreaking via Positive Affirmation, Negative Demonstration, and Adaptive Sampling. - Avery Ma; Yangchen Pan; Amir-massoud Farahmand (CoRR, 2025)

Measures of Variability for Risk-averse Policy Gradient. - Yudong Luo; Yangchen Pan; Jiaqi Tan 005; Pascal Poupart (CoRR, 2025)