Adam White

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 42

Top Topics

State Variables

Confidence Measures

Recurrent Neural Networks

Reinforcement Learning

Top Venues

J. Artif. Intell. Res.

Publications

David Rolnick, Alán Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L. Donti, Marzyeh Ghassemi, Hannah Kerner, Claire Monteleoni, Esther Rolf, Milind Tambe, Adam White
Application-Driven Innovation in Machine Learning. CoRR (2024)
Muhammad Kamran Janjua, Haseeb Shah, Martha White, Erfan Miahi, Marlos C. Machado, Adam White
GVFs in the Real World: Making Predictions Online for Water Treatment. CoRR (2023)
Andrew Patterson, Samuel Neumann, Martha White, Adam White
Empirical Design in Reinforcement Learning. CoRR (2023)
Matthew McLeod, Chunlok Lo, Matthew Schlegel, Andrew Jacobsen, Raksha Kumaraswamy, Martha White, Adam White
Continual Auxiliary Task Learning. CoRR (2022)
Richard S. Sutton, Marlos C. Machado, G. Zacharias Holland, David Szepesvari, Finbarr Timbers, Brian Tanner, Adam White
Reward-Respecting Subtasks for Model-Based Reinforcement Learning. CoRR (2022)
Andrew Butcher, Michael Bradley Johanson, Elnaz Davoodi, Dylan J. A. Brenneis, Leslie Acker, Adam S. R. Parker, Adam White, Joseph Modayil, Patrick M. Pilarski
Pavlovian Signalling with General Value Functions in Agent-Agent Temporal Decision Making. CoRR (2022)
Dylan J. A. Brenneis, Adam S. R. Parker, Michael Bradley Johanson, Andrew Butcher, Elnaz Davoodi, Leslie Acker, Matthew M. Botvinick, Joseph Modayil, Adam White, Patrick M. Pilarski
Assessing Human Interaction in Virtual Reality With Continually Learning Prediction Agents Based on Reinforcement Learning Algorithms: A Pilot Study. CoRR (2021)
Adam White, Kwun Ho Ngan, James Phelan, Saman Sadeghi Afgeh, Kevin Ryan, Constantino Carlos Reyes-Aldasoro, Artur d'Avila Garcez
Contrastive Counterfactual Visual Explanations With Overdetermination. CoRR (2021)
Adam White, Artur d'Avila Garcez
Counterfactual Instances Explain Little. CoRR (2021)
Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt
Emphatic Algorithms for Deep Reinforcement Learning. ICML (2021)
Matthew Schlegel, Andrew Jacobsen, Zaheer Abbas, Andrew Patterson, Adam White, Martha White
General Value Function Networks. J. Artif. Intell. Res. 70 (2021)
Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt
Emphatic Algorithms for Deep Reinforcement Learning. CoRR (2021)
Ray Jiang, Shangtong Zhang, Veronica Chelu, Adam White, Hado van Hasselt
Learning Expected Emphatic Traces for Deep RL. CoRR (2021)
Andrew Patterson, Adam White, Sina Ghiassian, Martha White
A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning. CoRR (2021)
Sina Ghiassian, Banafsheh Rafiee, Yat Long Lo, Adam White
Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks. CoRR (2020)
Adam White, Artur S. d'Avila Garcez
Measurable Counterfactual Local Explanations for Any Classifier. ECAI (2020)
Sina Ghiassian, Andrew Patterson, Shivam Garg, Dhawal Gupta, Adam White, Martha White
Gradient Temporal-Difference Learning with Regularized Corrections. ICML (2020)
Anita Samarth, Kevin Chaney, Dave Levin, Adam White, Ricky Sahu
API Connectivity: Real-World Uses and Implementation Experiences in using APIs and Third-party Apps for Data Exchange and Research. AMIA (2020)
Sina Ghiassian, Andrew Patterson, Shivam Garg, Dhawal Gupta, Adam White, Martha White
Gradient Temporal-Difference Learning with Regularized Corrections. CoRR (2020)
Vincent Liu, Adam White, Hengshuai Yao, Martha White
Towards a practical measure of interference for reinforcement learning. CoRR (2020)
Cam Linke, Nadia M. Ady, Martha White, Thomas Degris, Adam White
Adapting Behavior via Intrinsic Reward: A Survey and Empirical Study. J. Artif. Intell. Res. 69 (2020)
Somjit Nath, Vincent Liu, Alan Chan, Xin Li, Adam White, Martha White
Training Recurrent Neural Networks Online by Learning Explicit State Variables. ICLR (2020)
Sina Ghiassian, Banafsheh Rafiee, Yat Long Lo, Adam White
Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks. AAMAS (2020)
Cam Linke, Nadia M. Ady, Martha White, Thomas Degris, Adam White
Adapting Behaviour via Intrinsic Reward: A Survey and Empirical Study. CoRR (2019)
Yi Wan, Muhammad Zaheer, Adam White, Martha White, Richard S. Sutton
Planning with Expectation Models. IJCAI (2019)
Adam White, Artur S. d'Avila Garcez
Measurable Counterfactual Local Explanations for Any Classifier. CoRR (2019)
Yi Wan, Muhammad Zaheer, Adam White, Martha White, Richard S. Sutton
Planning with Expectation Models. CoRR (2019)
Andrew Jacobsen, Matthew Schlegel, Cameron Linke, Thomas Degris, Adam White, Martha White
Meta-Descent for Online, Continual Prediction. AAAI (2019)
Banafsheh Rafiee, Sina Ghiassian, Adam White, Richard S. Sutton
Prediction in Intelligence: An Empirical Comparison of Off-policy Algorithms on Robots. AAMAS (2019)
Andrew Jacobsen, Matthew Schlegel, Cameron Linke, Thomas Degris, Adam White, Martha White
Meta-descent for Online, Continual Prediction. CoRR (2019)
Raksha Kumaraswamy, Matthew Schlegel, Adam White, Martha White
Context-Dependent Upper-Confidence Bounds for Directed Exploration. CoRR (2018)
Matthew Schlegel, Adam White, Andrew Patterson, Martha White
General Value Function Networks. CoRR (2018)
Craig Sherstan, Brendan Bennett, Kenny Young, Dylan R. Ashley, Adam White, Martha White, Richard S. Sutton
Directly Estimating the Variance of the λ-Return Using Temporal-Difference Methods. CoRR (2018)
Tom Schaul, Hado van Hasselt, Joseph Modayil, Martha White, Adam White, Pierre-Luc Bacon, Jean Harb, Shibl Mourad, Marc G. Bellemare, Doina Precup
The Barbados 2018 List of Open Issues in Continual Learning. CoRR (2018)
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)
Sina Ghiassian, Andrew Patterson, Martha White, Richard S. Sutton, Adam White
Online Off-policy Prediction. CoRR (2018)
Craig Sherstan, Dylan R. Ashley, Brendan Bennett, Kenny Young, Adam White, Martha White, Richard S. Sutton
Comparing Direct and Indirect Temporal-Difference Methods for Estimating the Variance of the Return. UAI (2018)
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 (2018)
Raksha Kumaraswamy, Matthew Schlegel, Adam White, Martha White
Context-dependent upper-confidence bounds for directed exploration. NeurIPS (2018)
Adam White, Richard S. Sutton
GQ($λ$) Quick Reference and Implementation Guide. CoRR (2017)
Craig Sherstan, Adam White, Marlos C. Machado, Patrick M. Pilarski
Introspective Agents: Confidence Measures for General Value Functions. AGI (2016)
Craig Sherstan, Adam White, Marlos C. Machado, Patrick M. Pilarski
Introspective Agents: Confidence Measures for General Value Functions. CoRR (2016)
Joseph Modayil, Adam White, Richard S. Sutton
Multi-timescale nexting in a reinforcement learning robot. Adapt. Behav. 22 (2) (2014)
Steven J. Johnston, Neil S. O'Brien, Hugh G. Lewis, Elizabeth E. Hart, Adam White, Simon J. Cox
Clouds in Space: Scientific Computing using Windows Azure. J. Cloud Comput. 2 (2013)
Adam White, Joseph Modayil, Richard S. Sutton
Scaling Life-long Off-policy Learning CoRR (2012)
Adam White, Joseph Modayil, Richard S. Sutton
Scaling life-long off-policy learning. ICDL-EPIROB (2012)
Joseph Modayil, Adam White, Patrick M. Pilarski, Richard S. Sutton
Acquiring a broad range of empirical knowledge in real time by temporal-difference learning. SMC (2012)
Joseph Modayil, Adam White, Richard S. Sutton
Multi-timescale Nexting in a Reinforcement Learning Robot. SAB (2012)
Joseph Modayil, Adam White, Richard S. Sutton
Multi-timescale Nexting in a Reinforcement Learning Robot CoRR (2011)
Richard S. Sutton, Joseph Modayil, Michael Delp, Thomas Degris, Patrick M. Pilarski, Adam White, Doina Precup
Horde: a scalable real-time architecture for learning knowledge from unsupervised sensorimotor interaction. AAMAS (2011)