White, Adam

33 publications

ICML 2025 Position: Lifetime Tuning Is Incompatible with Continual Reinforcement Learning Golnaz Mesbahi, Parham Mohammad Panahi, Olya Mastikhina, Steven Tang, Martha White, Adam White

NeurIPS 2024 A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning Jacob Adkins, Michael Bowling, Adam White

TMLR 2024 AGaLiTe: Approximate Gated Linear Transformers for Online Reinforcement Learning Subhojeet Pramanik, Esraa Elelimy, Marlos C. Machado, Adam White

JMLR 2024 Empirical Design in Reinforcement Learning Andrew Patterson, Samuel Neumann, Martha White, Adam White

MLJ 2024 GVFs in the Real World: Making Predictions Online for Water Treatment Muhammad Kamran Janjua, Haseeb Shah, Martha White, Erfan Miahi, Marlos C. Machado, Adam White

JMLR 2024 Goal-Space Planning with Subgoal Models Chunlok Lo, Kevin Roice, Parham Mohammad Panahi, Scott M. Jordan, Adam White, Gabor Mihucz, Farzane Aminmansour, Martha White

ICML 2024 Position: Application-Driven Innovation in Machine Learning David Rolnick, Alan Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L. Donti, Marzyeh Ghassemi, Hannah Kerner, Claire Monteleoni, Esther Rolf, Milind Tambe, Adam White

ICML 2024 Position: Benchmarking Is Limited in Reinforcement Learning Research Scott M. Jordan, Adam White, Bruno Castro Da Silva, Martha White, Philip S. Thomas

NeurIPS 2024 Real-Time Recurrent Learning Using Trace Units in Reinforcement Learning Esraa Elelimy, Adam White, Michael Bowling, Martha White

AAAI 2024 Reward-Respecting Subtasks for Model-Based Reinforcement Learning (Abstract Reprint) Richard S. Sutton, Marlos C. Machado, G. Zacharias Holland, David Szepesvari, Finbarr Timbers, Brian Tanner, Adam White

TMLR 2023 Agent-State Construction with Auxiliary Inputs Ruo Yu Tao, Adam White, Marlos C. Machado

CoLLAs 2023 Auxiliary Task Discovery Through Generate-and-Test Banafsheh Rafiee, Sina Ghiassian, Jun Jin, Richard Sutton, Jun Luo, Adam White

MLJ 2023 Contrastive Counterfactual Visual Explanations with Overdetermination Adam White, Kwun Ho Ngan, James Phelan, Kevin Ryan, Saman Sadeghi Afgeh, Constantino Carlos Reyes-Aldasoro, Artur S. d'Avila Garcez

ICLR 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

CoLLAs 2023 Loss of Plasticity in Continual Deep Reinforcement Learning Zaheer Abbas, Rosie Zhao, Joseph Modayil, Adam White, Marlos C. Machado

CoLLAs 2023 Measuring and Mitigating Interference in Reinforcement Learning Vincent Liu, Han Wang, Ruo Yu Tao, Khurram Javed, Adam White, Martha White

ICLR 2023 The In-Sample SoftMax for Offline Reinforcement Learning Chenjun Xiao, Han Wang, Yangchen Pan, Adam White, Martha White

JMLR 2022 A Generalized Projected Bellman Error for Off-Policy Value Estimation in Reinforcement Learning Andrew Patterson, Adam White, Martha White

AAAI 2022 Learning Expected Emphatic Traces for Deep RL Ray Jiang, Shangtong Zhang, Veronica Chelu, Adam White, Hado van Hasselt

NeurIPS 2021 Continual Auxiliary Task Learning Matthew McLeod, Chunlok Lo, Matthew Schlegel, Andrew Jacobsen, Raksha Kumaraswamy, Martha White, Adam White

ICML 2021 Emphatic Algorithms for Deep Reinforcement Learning Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado Van Hasselt

JAIR 2021 General Value Function Networks Matthew Schlegel, Andrew Jacobsen, Zaheer Abbas, Andrew Patterson, Adam White, Martha White

JAIR 2020 Adapting Behavior via Intrinsic Reward: A Survey and Empirical Study Cam Linke, Nadia M. Ady, Martha White, Thomas Degris, Adam White

ICML 2020 Gradient Temporal-Difference Learning with Regularized Corrections Sina Ghiassian, Andrew Patterson, Shivam Garg, Dhawal Gupta, Adam White, Martha White

ICLR 2020 Training Recurrent Neural Networks Online by Learning Explicit State Variables Somjit Nath, Vincent Liu, Alan Chan, Xin Li, Adam White, Martha White

AAAI 2019 Meta-Descent for Online, Continual Prediction Andrew Jacobsen, Matthew Schlegel, Cameron Linke, Thomas Degris, Adam White, Martha White

IJCAI 2019 Planning with Expectation Models Yi Wan, Muhammad Zaheer, Adam White, Martha White, Richard S. Sutton

UAI 2018 Comparing Direct and Indirect Temporal-Difference Methods for Estimating the Variance of the Return Craig Sherstan, Dylan R. Ashley, Brendan Bennett, Kenny Young, Adam White, Martha White, Richard S. Sutton

NeurIPS 2018 Context-Dependent Upper-Confidence Bounds for Directed Exploration Raksha Kumaraswamy, Matthew Schlegel, Adam White, Martha White

IJCAI 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

AAAI 2017 Accelerated Gradient Temporal Difference Learning Yangchen Pan, Adam White, Martha White

NeurIPS 2010 Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains Martha White, Adam White

MLOSS 2009 RL-GLUE: Language-Independent Software for Reinforcement-Learning Experiments Brian Tanner, Adam White