Optimal reverse prediction: a unified perspective on supervised, unsupervised and semi-supervised learning. - Linli Xu; Martha White; Dale Schuurmans (ICML, 2009)

Learning a Value Analysis Tool for Agent Evaluation. - Martha White; Michael H. Bowling (IJCAI, 2009)

Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains. - Martha White; Adam White 001 (NIPS, 2010)

Relaxed Clipping: A Global Training Method for Robust Regression and Classification. - Yaoliang Yu; Min Yang; Linli Xu; Martha White; Dale Schuurmans (NIPS, 2010)

Convex Sparse Coding, Subspace Learning, and Semi-Supervised Extensions. - Xinhua Zhang; Yaoliang Yu; Martha White; Ruitong Huang; Dale Schuurmans (AAAI, 2011)

Linear Off-Policy Actor-Critic. - Thomas Degris; Martha White; Richard S. Sutton (ICML, 2012)

Convex Multi-view Subspace Learning. - Martha White; Yaoliang Yu; Xinhua Zhang; Dale Schuurmans (NIPS, 2012)

Off-Policy Actor-Critic - Thomas Degris; Martha White; Richard S. Sutton (CoRR, 2012)

Generalized Optimal Reverse Prediction. - Martha White; Dale Schuurmans (AISTATS, 2012)

Partition Tree Weighting. - Joel Veness; Martha White; Michael Bowling; András György 001 (DCC, 2013)

Optimal Estimation of Multivariate ARMA Models. - Martha White; Junfeng Wen; Michael Bowling; Dale Schuurmans (AAAI, 2015)

Scalable Metric Learning for Co-Embedding. - Farzaneh Mirzazadeh; Martha White; András György 001; Dale Schuurmans (ECML/PKDD (1), 2015)

Incremental Truncated LSTD. - Clement Gehring; Martha White (CoRR, 2015)

Emphatic Temporal-Difference Learning. - Ashique Rupam Mahmood; Huizhen Yu; Martha White; Richard S. Sutton (CoRR, 2015)

Investigating Practical Linear Temporal Difference Learning. - Adam White 001; Martha White (AAMAS, 2016)

A Greedy Approach to Adapting the Trace Parameter for Temporal Difference Learning. - Martha White; Adam White 001 (AAMAS, 2016)

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

Estimating the class prior and posterior from noisy positives and unlabeled data. - Shantanu Jain; Martha White; Predrag Radivojac (NIPS, 2016)

Nonparametric semi-supervised learning of class proportions. - Shantanu Jain; Martha White; Michael W. Trosset; Predrag Radivojac (CoRR, 2016)

Global optimization of factor models using alternating minimization. - Lei Le; Martha White (CoRR, 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)

Recovering True Classifier Performance in Positive-Unlabeled Learning. - Shantanu Jain; Martha White; Predrag Radivojac (AAAI, 2017)

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)

Unifying Task Specification in Reinforcement Learning. - Martha White (ICML, 2017)

Learning Sparse Representations in Reinforcement Learning with Sparse Coding. - Lei Le; Raksha Kumaraswamy; Martha White (IJCAI, 2017)

Multi-view Matrix Factorization for Linear Dynamical System Estimation. - Mahdi Karami; Martha White; Dale Schuurmans; Csaba Szepesvári (NIPS, 2017)

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

Improving Regression Performance with Distributional Losses. - Ehsan Imani; Martha White (ICML, 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 (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)

An Off-policy Policy Gradient Theorem Using Emphatic Weightings. - Ehsan Imani; Eric Graves 002; Martha White (NeurIPS, 2018)

Context-dependent upper-confidence bounds for directed exploration. - Raksha Kumaraswamy; Matthew Schlegel; Adam White 001; Martha White (NeurIPS, 2018)

Supervised autoencoders: Improving generalization performance with unsupervised regularizers. - Lei Le; Andrew Patterson; Martha White (NeurIPS, 2018)

High-confidence error estimates for learned value functions. - Touqir Sajed; Wesley Chung; Martha White (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 001; Martha White; Richard S. Sutton (UAI, 2018)

Directly Estimating the Variance of the λ-Return Using Temporal-Difference Methods. - Craig Sherstan; Brendan Bennett; Kenny Young; Dylan R. Ashley; Adam White 001; Martha White; Richard S. Sutton (CoRR, 2018)

General Value Function Networks. - Matthew Schlegel; Adam White 001; Andrew Patterson; Martha White (CoRR, 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)

Online Off-policy Prediction. - Sina Ghiassian; Andrew Patterson; Martha White; Richard S. Sutton; Adam White 001 (CoRR, 2018)

The Barbados 2018 List of Open Issues in Continual Learning. - Tom Schaul; Hado van Hasselt; Joseph Modayil; Martha White; Adam White 001; Pierre-Luc Bacon; Jean Harb; Shibl Mourad; Marc G. Bellemare; Doina Precup (CoRR, 2018)

Accelerating Large Scale Knowledge Distillation via Dynamic Importance Sampling. - Minghan Li 002; Tanli Zuo; Ruicheng Li; Martha White; Weishi Zheng 001 (CoRR, 2018)

Meta-Descent for Online, Continual Prediction. - Andrew Jacobsen; Matthew Schlegel; Cameron Linke; Thomas Degris; Adam White 001; Martha White (AAAI, 2019)

The Utility of Sparse Representations for Control in Reinforcement Learning. - Vincent Liu; Raksha Kumaraswamy; Lei Le; Martha White (AAAI, 2019)

Two-Timescale Networks for Nonlinear Value Function Approximation. - Wesley Chung; Somjit Nath; Ajin Joseph 001; Martha White (ICLR (Poster), 2019)

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

Planning with Expectation Models. - Yi Wan 004; Muhammad Zaheer; Adam White 001; Martha White; Richard S. Sutton (IJCAI, 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 (NeurIPS, 2019)

Meta-Learning Representations for Continual Learning. - Khurram Javed; Martha White (NeurIPS, 2019)

Importance Resampling for Off-policy Prediction. - Matthew Schlegel; Wesley Chung; Daniel Graves; Jian Qian; Martha White (NeurIPS, 2019)

Adapting Behaviour via Intrinsic Reward: A Survey and Empirical Study. - Cam Linke; Nadia M. Ady; Martha White; Thomas Degris; Adam White 001 (CoRR, 2019)

Is Fast Adaptation All You Need? - Khurram Javed; Hengshuai Yao; Martha White (CoRR, 2019)

Maximizing Information Gain in Partially Observable Environments via Prediction Rewards. - Yash Satsangi; Sungsu Lim; Shimon Whiteson; Frans A. Oliehoek; Martha White (AAMAS, 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 (EMNLP (Findings), 2020)

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

Training Recurrent Neural Networks Online by Learning Explicit State Variables. - Somjit Nath; Vincent Liu; Alan Chan 001; Xin Li; Adam White 001; Martha White (ICLR, 2020)

Selective Dyna-Style Planning Under Limited Model Capacity. - Zaheer Abbas; Samuel Sokota; Erin Talvitie; Martha White (ICML, 2020)

Optimizing for the Future in Non-Stationary MDPs. - Yash Chandak; Georgios Theocharous; Shiv Shankar; Martha White; Sridhar Mahadevan; Philip S. Thomas (ICML, 2020)

Gradient Temporal-Difference Learning with Regularized Corrections. - Sina Ghiassian; Andrew Patterson; Shivam Garg 006; Dhawal Gupta; Adam White 001; Martha White (ICML, 2020)

Towards Safe Policy Improvement for Non-Stationary MDPs. - Yash Chandak; Scott M. Jordan; Georgios Theocharous; Martha White; Philip S. Thomas (NeurIPS, 2020)

An implicit function learning approach for parametric modal regression. - Yangchen Pan; Ehsan Imani; Amir-massoud Farahmand; Martha White (NeurIPS, 2020)

Maximizing Information Gain in Partially Observable Environments via Prediction Reward. - Yash Satsangi; Sungsu Lim; Shimon Whiteson; Frans A. Oliehoek; Martha White (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)

Learning Causal Models Online. - Khurram Javed; Martha White; Yoshua Bengio (CoRR, 2020)

Towards a practical measure of interference for reinforcement learning. - Vincent Liu; Adam White 001; Hengshuai Yao; Martha White (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)

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)

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 001; et al. (CoRR, 2020)

Adapting Behavior via Intrinsic Reward: A Survey and Empirical Study. - Cam Linke; Nadia M. Ady; Martha White; Thomas Degris; Adam White 001 (J. Artif. Intell. Res., 2020)

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

Structural Credit Assignment in Neural Networks using Reinforcement Learning. - Dhawal Gupta; Gabor Mihucz; Matthew Schlegel; James E. Kostas; Philip S. Thomas; Martha White (NeurIPS, 2021)

Continual Auxiliary Task Learning. - Matthew McLeod; Chunlok Lo; Matthew Schlegel; Andrew Jacobsen; Raksha Kumaraswamy; Martha White; Adam White 001 (NeurIPS, 2021)

Scalable Online Recurrent Learning Using Columnar Neural Networks. - Khurram Javed; Martha White; Richard S. Sutton (CoRR, 2021)

A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning. - Andrew Patterson; Adam White 001; Sina Ghiassian; Martha White (CoRR, 2021)

Predictive Representation Learning for Language Modeling. - Qingfeng Lan; Luke Kumar; Martha White; Alona Fyshe (CoRR, 2021)

Exploiting Action Impact Regularity and Partially Known Models for Offline Reinforcement Learning. - Vincent Liu; James R. Wright; Martha White (CoRR, 2021)

Understanding Feature Transfer Through Representation Alignment. - Ehsan Imani; Wei Hu; Martha White (CoRR, 2021)

General Value Function Networks. - Matthew Schlegel; Andrew Jacobsen; Zaheer Abbas; Andrew Patterson; Adam White 001; Martha White (J. Artif. Intell. Res., 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 001; et al. (IEEE Trans Autom. Sci. Eng., 2021)

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

Resonance in Weight Space: Covariate Shift Can Drive Divergence of SGD with Momentum. - Kirby Banman; Liam Peet-Pare; Nidhi Hegde 001; Alona Fyshe; Martha White (ICLR, 2022)

A Temporal-Difference Approach to Policy Gradient Estimation. - Samuele Tosatto; Andrew Patterson; Martha White; Rupam Mahmood (ICML, 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)

Goal-Space Planning with Subgoal Models. - Chunlok Lo; Gabor Mihucz; Adam White 001; Farzane Aminmansour; Martha White (CoRR, 2022)

Greedification Operators for Policy Optimization: Investigating Forward and Reverse KL Divergences. - Alan Chan 001; Hugo Silva; Sungsu Lim; Tadashi Kozuno; A. Rupam Mahmood; Martha White (J. Mach. Learn. Res., 2022)

A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning. - Andrew Patterson; Adam White 001; Martha White (J. Mach. Learn. Res., 2022)

Representation Alignment in Neural Networks. - Ehsan Imani; Wei Hu; Martha White (Trans. Mach. Learn. Res., 2022)

No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL. - Han Wang; Archit Sakhadeo; Adam M. White; James Bell 004; Vincent Liu; Xutong Zhao; Puer Liu; Tadashi Kozuno; Alona Fyshe; Martha White (Trans. Mach. Learn. Res., 2022)

Asymptotically Unbiased Off-Policy Policy Evaluation when Reusing Old Data in Nonstationary Environments. - Vincent Liu; Yash Chandak; Philip S. Thomas; Martha White (AISTATS, 2023)

Measuring and Mitigating Interference in Reinforcement Learning. - Vincent Liu; Han Wang; Ruo Yu Tao; Khurram Javed; Adam White 001; Martha White (CoLLAs, 2023)

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)

Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning. - Brett Daley; Martha White; Christopher Amato; Marlos C. Machado (ICML, 2023)

General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence. - Lingwei Zhu; Zheng Chen 012; Matthew Schlegel; Martha White (NeurIPS, 2023)

Generalized Munchausen Reinforcement Learning using Tsallis KL Divergence. - Lingwei Zhu; Zheng Chen 012; Takamitsu Matsubara; Martha 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)

Empirical Design in Reinforcement Learning. - Andrew Patterson; Samuel Neumann; Martha White; Adam White 001 (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)

When is Offline Policy Selection Sample Efficient for Reinforcement Learning? - Vincent Liu; Prabhat Nagarajan; Andrew Patterson; Martha White (CoRR, 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)

Off-Policy Actor-Critic with Emphatic Weightings. - Eric Graves 002; Ehsan Imani; Raksha Kumaraswamy; Martha White (J. 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)

Resmax: An Alternative Soft-Greedy Operator for Reinforcement Learning. - Erfan Miahi; Revan MacQueen; Alex Ayoub; Abbas Masoumzadeh; Martha White (Trans. Mach. Learn. Res., 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)

Robust Losses for Learning Value Functions. - Andrew Patterson; Victor Liao; Martha White (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Exploiting Action Impact Regularity and Exogenous State Variables for Offline Reinforcement Learning (Abstract Reprint). - Vincent Liu; James R. Wright; Martha White (AAAI, 2024)

Averaging n-step Returns Reduces Variance in Reinforcement Learning. - Brett Daley; Martha White; Marlos C. Machado (ICML, 2024)

Position: Benchmarking is Limited in Reinforcement Learning Research. - Scott M. Jordan; Adam White 001; Bruno Castro da Silva; Martha White; Philip S. Thomas (ICML, 2024)

Real-Time Recurrent Learning using Trace Units in Reinforcement Learning. - Esraa Elelimy; Adam White 001; Michael Bowling; Martha White (NeurIPS, 2024)

Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers. - Gautham Vasan; Mohamed Elsayed 003; Seyed Alireza Azimi; Jiamin He; Fahim Shahriar; Colin Bellinger; Martha White; Rupam Mahmood (NeurIPS, 2024)

Demystifying the Recency Heuristic in Temporal-Difference Learning. - Brett Daley; Marlos C. Machado; Martha White (RLJ, 2024)

Investigating the Interplay of Prioritized Replay and Generalization. - Parham Mohammad Panahi; Andrew Patterson; Martha White; Adam White 001 (RLJ, 2024)

Cross-environment Hyperparameter Tuning for Reinforcement Learning. - Andrew Patterson; Samuel Neumann; Raksha Kumaraswamy; Martha White; Adam White 001 (RLJ, 2024)

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 001 (Artif. Intell., 2024)

Compound Returns Reduce Variance in Reinforcement Learning. - Brett Daley; Martha White; Marlos C. Machado (CoRR, 2024)

What to Do When Your Discrete Optimization Is the Size of a Neural Network? - Hugo Silva; Martha White (CoRR, 2024)

Investigating the Histogram Loss in Regression. - Ehsan Imani; Kai Luedemann; Sam Scholnick-Hughes; Esraa Elelimy; Martha White (CoRR, 2024)

Tuning for the Unknown: Revisiting Evaluation Strategies for Lifelong RL. - Golnaz Mesbahi; Olya Mastikhina; Parham Mohammad Panahi; Martha White; Adam White 001 (CoRR, 2024)

A New View on Planning in Online Reinforcement Learning. - Kevin Roice; Parham Mohammad Panahi; Scott M. Jordan; Adam White 001; Martha White (CoRR, 2024)

The Cross-environment Hyperparameter Setting Benchmark for Reinforcement Learning. - Andrew Patterson; Samuel Neumann; Raksha Kumaraswamy; Martha White; Adam White 001 (CoRR, 2024)

q-exponential family for policy optimization. - Lingwei Zhu; Haseeb Shah; Han Wang; Martha White (CoRR, 2024)

Mitigating Value Hallucination in Dyna-Style Planning via Multistep Predecessor Models. - Farzane Aminmansour; Taher Jafferjee; Ehsan Imani; Erin J. Talvitie; Michael Bowling; Martha White (J. Artif. Intell. Res., 2024)

Offline Reinforcement Learning via Tsallis Regularization. - Lingwei Zhu; Matthew Schlegel; Han Wang; Martha White (Trans. Mach. Learn. Res., 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 001 (Mach. Learn., 2024)

q-exponential family for policy optimization. - Lingwei Zhu; Haseeb Shah; Han Wang; Yukie Nagai; Martha White (ICLR, 2025)

Fine-Tuning without Performance Degradation. - Han Wang; Adam White 001; Martha White (CoRR, 2025)

Distribution Parameter Actor-Critic: Shifting the Agent-Environment Boundary for Diverse Action Spaces. - Jiamin He; A. Rupam Mahmood; Martha White (CoRR, 2025)

Double Q-learning for Value-based Deep Reinforcement Learning, Revisited. - Prabhat Nagarajan; Martha White; Marlos C. Machado (CoRR, 2025)

Deep Reinforcement Learning with Gradient Eligibility Traces. - Esraa Elelimy; Brett Daley; Andrew Patterson; Marlos C. Machado; Adam White 001; Martha White (CoRR, 2025)

An Analysis of Action-Value Temporal-Difference Methods That Learn State Values. - Brett Daley; Prabhat Nagarajan; Martha White; Marlos C. Machado (CoRR, 2025)

PC-Gym: Benchmark environments for process control problems. - Maximilian Bloor; José Torraca; Ilya Orson Sandoval; Akhil Ahmed; Martha White; Mehmet Mercangöz; Calvin Tsay; Ehecatl Antonio del Rio-Chanona; Max Mowbray (Comput. Chem. Eng., 2026)