Martha White

According to our database, Martha White authored at least 110 papers between 2009 and 2024.

Collaborative distances:

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

2024

Investigating the Histogram Loss in Regression.

Ehsan Imani, Kai Luedemann, Sam Scholnick-Hughes, Esraa Elelimy, Martha White

CoRR, 2024

What to Do When Your Discrete Optimization Is the Size of a Neural Network?

Hugo Silva, Martha White

CoRR, 2024

Compound Returns Reduce Variance in Reinforcement Learning.

Brett Daley, Martha White, Marlos C. Machado

CoRR, 2024

Exploiting Action Impact Regularity and Exogenous State Variables for Offline Reinforcement Learning (Abstract Reprint).

Vincent Liu, James R. Wright, Martha White

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Robust Losses for Learning Value Functions.

Andrew Patterson, Victor Liao, Martha White

IEEE Trans. Pattern Anal. Mach. Intell., May, 2023

Investigating Action Encodings in Recurrent Neural Networks in Reinforcement Learning.

Matthew Schlegel, Volodymyr Tkachuk, Adam M. White, Martha White

Trans. Mach. Learn. Res., 2023

Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks.

Khurram Javed, Haseeb Shah, Richard S. Sutton, Martha White

J. Mach. Learn. Res., 2023

Off-Policy Actor-Critic with Emphatic Weightings.

Eric Graves, Ehsan Imani, Raksha Kumaraswamy, Martha White

J. Mach. Learn. Res., 2023

Exploiting Action Impact Regularity and Exogenous State Variables for Offline Reinforcement Learning.

Vincent Liu, James R. Wright, Martha White

J. Artif. Intell. Res., 2023

When is Offline Policy Selection Sample Efficient for Reinforcement Learning?

Vincent Liu, Prabhat Nagarajan, Andrew Patterson, Martha White

CoRR, 2023

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

CoRR, 2023

Coagent Networks: Generalized and Scaled.

James E. Kostas, Scott M. Jordan, Yash Chandak, Georgios Theocharous, Dhawal Gupta, Martha White, Bruno Castro da Silva, Philip S. Thomas

CoRR, 2023

Empirical Design in Reinforcement Learning.

Andrew Patterson, Samuel Neumann, Martha White, Adam White

CoRR, 2023

Online Real-Time Recurrent Learning Using Sparse Connections and Selective Learning.

Khurram Javed, Haseeb Shah, Richard S. Sutton, Martha White

CoRR, 2023

Generalized Munchausen Reinforcement Learning using Tsallis KL Divergence.

Lingwei Zhu, Zheng Chen, Takamitsu Matsubara, Martha White

CoRR, 2023

General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence.

Lingwei Zhu, Zheng Chen, Matthew Schlegel, Martha White

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

Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning.

Brett Daley, Martha White, Christopher Amato, Marlos C. Machado

Proceedings of the International Conference on Machine Learning, 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

Measuring and Mitigating Interference in Reinforcement Learning.

Vincent Liu, Han Wang, Ruo Yu Tao, Khurram Javed, Adam White, Martha White

Proceedings of the Conference on Lifelong Learning Agents, 2023

Asymptotically Unbiased Off-Policy Policy Evaluation when Reusing Old Data in Nonstationary Environments.

Vincent Liu, Yash Chandak, Philip S. Thomas, Martha White

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL.

Han Wang, Archit Sakhadeo, Adam M. White, James Bell, Vincent Liu, Xutong Zhao, Puer Liu, Tadashi Kozuno, Alona Fyshe, Martha White

Trans. Mach. Learn. Res., 2022

Representation Alignment in Neural Networks.

Ehsan Imani, Wei Hu, Martha White

Trans. Mach. Learn. Res., 2022

A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning.

Andrew Patterson, Adam White, Martha White

J. Mach. Learn. Res., 2022

Greedification Operators for Policy Optimization: Investigating Forward and Reverse KL Divergences.

Alan Chan, Hugo Silva, Sungsu Lim, Tadashi Kozuno, A. Rupam Mahmood, Martha White

J. Mach. Learn. Res., 2022

Goal-Space Planning with Subgoal Models.

Chunlok Lo, Gabor Mihucz, Adam White, Farzane Aminmansour, Martha White

CoRR, 2022

Investigating the Properties of Neural Network Representations in Reinforcement Learning.

Han Wang, Erfan Miahi, Martha White, Marlos C. Machado, Zaheer Abbas, Raksha Kumaraswamy, Vincent Liu, Adam White

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

A Temporal-Difference Approach to Policy Gradient Estimation.

Samuele Tosatto, Andrew Patterson, Martha White, Rupam Mahmood

Proceedings of the International Conference on Machine Learning, 2022

Resonance in Weight Space: Covariate Shift Can Drive Divergence of SGD with Momentum.

Kirby Banman, Liam Peet-Pare, Nidhi Hegde, Alona Fyshe, Martha White

Proceedings of the Tenth International Conference on Learning Representations, 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

Sim2Real in Robotics and Automation: Applications and Challenges.

Sebastian Höfer, Kostas E. Bekris, Ankur Handa, Juan Camilo Gamboa, Melissa Mozifian, Florian Golemo, Christopher G. Atkeson, Dieter Fox, Ken Goldberg, John Leonard, C. Karen Liu, Jan Peters, Shuran Song, Peter Welinder, Martha White

IEEE Trans Autom. Sci. Eng., 2021

General Value Function Networks.

Matthew Schlegel, Andrew Jacobsen, Zaheer Abbas, Andrew Patterson, Adam White, Martha White

J. Artif. Intell. Res., 2021

Understanding Feature Transfer Through Representation Alignment.

Ehsan Imani, Wei Hu, Martha White

CoRR, 2021

Exploiting Action Impact Regularity and Partially Known Models for Offline Reinforcement Learning.

Vincent Liu, James R. Wright, Martha White

CoRR, 2021

Predictive Representation Learning for Language Modeling.

Qingfeng Lan, Luke Kumar, Martha White, Alona Fyshe

CoRR, 2021

A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning.

Andrew Patterson, Adam White, Sina Ghiassian, Martha White

CoRR, 2021

Scalable Online Recurrent Learning Using Columnar Neural Networks.

Khurram Javed, Martha White, Richard S. Sutton

CoRR, 2021

Continual Auxiliary Task Learning.

Matthew McLeod, Chunlok Lo, Matthew Schlegel, Andrew Jacobsen, Raksha Kumaraswamy, Martha White, Adam White

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Structural Credit Assignment in Neural Networks using Reinforcement Learning.

Dhawal Gupta, Gabor Mihucz, Matthew Schlegel, James E. Kostas, Philip S. Thomas, Martha White

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 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

Adapting Behavior via Intrinsic Reward: A Survey and Empirical Study.

Cam Linke, Nadia M. Ady, Martha White, Thomas Degris, Adam White

J. Artif. Intell. Res., 2020

Perspectives on Sim2Real Transfer for Robotics: A Summary of the R: SS 2020 Workshop.

Sebastian Höfer, Kostas E. Bekris, Ankur Handa, Juan Camilo Gamboa Higuera, Florian Golemo, Melissa Mozifian, Christopher G. Atkeson, Dieter Fox, Ken Goldberg, John Leonard, C. Karen Liu, Jan Peters, Shuran Song, Peter Welinder, Martha White

CoRR, 2020

From Language to Language-ish: How Brain-Like is an LSTM's Representation of Nonsensical Language Stimuli?

Maryam Hashemzadeh, Greta Kaufeld, Martha White, Andrea E. Martin, Alona Fyshe

CoRR, 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

Towards a practical measure of interference for reinforcement learning.

Vincent Liu, Adam White, Hengshuai Yao, Martha White

CoRR, 2020

Learning Causal Models Online.

Khurram Javed, Martha White, Yoshua Bengio

CoRR, 2020

Hallucinating Value: A Pitfall of Dyna-style Planning with Imperfect Environment Models.

Taher Jafferjee, Ehsan Imani, Erin Talvitie, Martha White, Michael Bowling

CoRR, 2020

Maximizing Information Gain in Partially Observable Environments via Prediction Reward.

Yash Satsangi, Sungsu Lim, Shimon Whiteson, Frans A. Oliehoek, Martha White

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

Towards Safe Policy Improvement for Non-Stationary MDPs.

Yash Chandak, Scott M. Jordan, Georgios Theocharous, Martha White, Philip S. Thomas

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

Gradient Temporal-Difference Learning with Regularized Corrections.

Sina Ghiassian, Andrew Patterson, Shivam Garg, Dhawal Gupta, Adam White, Martha White

Proceedings of the 37th International Conference on Machine Learning, 2020

Optimizing for the Future in Non-Stationary MDPs.

Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip S. Thomas

Proceedings of the 37th International Conference on Machine Learning, 2020

Selective Dyna-Style Planning Under Limited Model Capacity.

Zaheer Abbas, Samuel Sokota, Erin Talvitie, Martha White

Proceedings of the 37th International Conference on Machine Learning, 2020

Training Recurrent Neural Networks Online by Learning Explicit State Variables.

Somjit Nath, Vincent Liu, Alan Chan, Xin Li, Adam White, Martha White

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

From Language to Language-ish: How Brain-Like is an LSTM's Representation of Atypical Language Stimuli?

Maryam Hashemzadeh, Greta Kaufeld, Martha White, Andrea E. Martin, Alona Fyshe

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Maximizing Information Gain in Partially Observable Environments via Prediction Rewards.

Yash Satsangi, Sungsu Lim, Shimon Whiteson, Frans A. Oliehoek, Martha White

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

Is Fast Adaptation All You Need?

Khurram Javed, Hengshuai Yao, Martha White

CoRR, 2019

Adapting Behaviour via Intrinsic Reward: A Survey and Empirical Study.

Cam Linke, Nadia M. Ady, Martha White, Thomas Degris, Adam White

CoRR, 2019

Importance Resampling for Off-policy Prediction.

Matthew Schlegel, Wesley Chung, Daniel Graves, Jian Qian, Martha White

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Meta-Learning Representations for Continual Learning.

Khurram Javed, Martha White

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning Macroscopic Brain Connectomes via Group-Sparse Factorization.

Farzane Aminmansour, Andrew Patterson, Lei Le, Yisu Peng, Daniel Mitchell, Franco Pestilli, Cesar F. Caiafa, Russell Greiner, Martha White

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Planning with Expectation Models.

Yi Wan, Muhammad Zaheer, Adam White, Martha White, Richard S. Sutton

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

Two-Timescale Networks for Nonlinear Value Function Approximation.

Wesley Chung, Somjit Nath, Ajin Joseph, Martha White

Proceedings of the 7th International Conference on Learning Representations, 2019

The Utility of Sparse Representations for Control in Reinforcement Learning.

Vincent Liu, Raksha Kumaraswamy, Lei Le, Martha White

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Meta-Descent for Online, Continual Prediction.

Andrew Jacobsen, Matthew Schlegel, Cameron Linke, Thomas Degris, Adam White, Martha White

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Accelerating Large Scale Knowledge Distillation via Dynamic Importance Sampling.

Minghan Li, Tanli Zuo, Ruicheng Li, Martha White, Weishi Zheng

CoRR, 2018

The Barbados 2018 List of Open Issues in Continual Learning.

Tom Schaul, Hado van Hasselt, Joseph Modayil, Martha White, Adam White, Pierre-Luc Bacon, Jean Harb, Shibl Mourad, Marc G. Bellemare, Doina Precup

CoRR, 2018

Online Off-policy Prediction.

Sina Ghiassian, Andrew Patterson, Martha White, Richard S. Sutton, Adam White

CoRR, 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

General Value Function Networks.

Matthew Schlegel, Adam White, Andrew Patterson, Martha White

CoRR, 2018

Directly Estimating the Variance of the λ-Return Using Temporal-Difference Methods.

Craig Sherstan, Brendan Bennett, Kenny Young, Dylan R. Ashley, Adam White, Martha White, Richard S. Sutton

CoRR, 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

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

High-confidence error estimates for learned value functions.

Touqir Sajed, Wesley Chung, Martha White

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Supervised autoencoders: Improving generalization performance with unsupervised regularizers.

Lei Le, Andrew Patterson, Martha White

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Context-dependent upper-confidence bounds for directed exploration.

Raksha Kumaraswamy, Matthew Schlegel, Adam White, Martha White

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

An Off-policy Policy Gradient Theorem Using Emphatic Weightings.

Ehsan Imani, Eric Graves, Martha White

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 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

Improving Regression Performance with Distributional Losses.

Ehsan Imani, Martha White

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

Multi-view Matrix Factorization for Linear Dynamical System Estimation.

Mahdi Karami, Martha White, Dale Schuurmans, Csaba Szepesvári

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning Sparse Representations in Reinforcement Learning with Sparse Coding.

Lei Le, Raksha Kumaraswamy, Martha White

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Unifying Task Specification in Reinforcement Learning.

Martha White

Proceedings of the 34th International Conference on Machine Learning, 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

Recovering True Classifier Performance in Positive-Unlabeled Learning.

Shantanu Jain, Martha White, Predrag Radivojac

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

2016

An Emphatic Approach to the Problem of Off-policy Temporal-Difference Learning.

Richard S. Sutton, Ashique Rupam Mahmood, Martha White

J. Mach. Learn. Res., 2016

Global optimization of factor models using alternating minimization.

Lei Le, Martha White

CoRR, 2016

Nonparametric semi-supervised learning of class proportions.

Shantanu Jain, Martha White, Michael W. Trosset, Predrag Radivojac

CoRR, 2016

Estimating the class prior and posterior from noisy positives and unlabeled data.

Shantanu Jain, Martha White, Predrag Radivojac

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Incremental Truncated LSTD.

Clement Gehring, Yangchen Pan, Martha White

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

A Greedy Approach to Adapting the Trace Parameter for Temporal Difference Learning.

Martha White, Adam White

Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

Investigating Practical Linear Temporal Difference Learning.

Adam White, Martha White

Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

2015

Emphatic Temporal-Difference Learning.

Ashique Rupam Mahmood, Huizhen Yu, Martha White, Richard S. Sutton

CoRR, 2015

Incremental Truncated LSTD.

Clement Gehring, Martha White

CoRR, 2015

Scalable Metric Learning for Co-Embedding.

Farzaneh Mirzazadeh, Martha White, András György, Dale Schuurmans

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Optimal Estimation of Multivariate ARMA Models.

Martha White, Junfeng Wen, Michael Bowling, Dale Schuurmans

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2013

Partition Tree Weighting.

Joel Veness, Martha White, Michael Bowling, András György

Proceedings of the 2013 Data Compression Conference, 2013

2012

Generalized Optimal Reverse Prediction.

Martha White, Dale Schuurmans

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Off-Policy Actor-Critic

Thomas Degris, Martha White, Richard S. Sutton

CoRR, 2012

Convex Multi-view Subspace Learning.

Martha White, Yaoliang Yu, Xinhua Zhang, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Linear Off-Policy Actor-Critic.

Thomas Degris, Martha White, Richard S. Sutton

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Convex Sparse Coding, Subspace Learning, and Semi-Supervised Extensions.

Xinhua Zhang, Yaoliang Yu, Martha White, Ruitong Huang, Dale Schuurmans

Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010

Relaxed Clipping: A Global Training Method for Robust Regression and Classification.

Yaoliang Yu, Min Yang, Linli Xu, Martha White, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains.

Martha White, Adam White

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009

Learning a Value Analysis Tool for Agent Evaluation.

Martha White, Michael H. Bowling

Proceedings of the IJCAI 2009, 2009

Optimal reverse prediction: a unified perspective on supervised, unsupervised and semi-supervised learning.

Linli Xu, Martha White, Dale Schuurmans

Proceedings of the 26th Annual International Conference on Machine Learning, 2009