Position: RL Researchers Need to Distinguish Between Solving Simulators and Using Simulators as a Proxy

International Conference on Machine Learning Position Paper Track (ICML) · 2026

Matthew Vandergrift, Esraa Elelimy, Martha White

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Investigating the Histogram Loss in Regression

Journal of Machine Learning Research (JMLR) · 2026

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

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Distributions as Actions: A Unified Framework for Diverse Action Spaces

International Conference on Learning Representations (ICLR) · 2026

Jiamin He, A. Rupam Mahmood, Martha White

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Regularized Latent Dynamics Prediction is a Strong Baseline For Behavioral Foundation Models

International Conference on Learning Representations (ICLR) · 2026

Pranaya Jajoo, Harshit Sikchi, S. Agarwal, Amy Zhang, Scott Niekum, Martha White

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When is Offline Policy Selection Sample Efficient for Reinforcement Learning?

International Conference on Autonomous Agents and Multiagent Systems (AAMAS), · 2026

Vincent Liu, Prabhat Nagarajan, Andrew Patterson, Martha White

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PC-Gym: Benchmark environments for process control problems

Computers & Chemical Engineering · 2026

M. Bloor, J. Torraca, I. O. Sandoval A. Ahmed, M. White, M. Mercangoz, C. Tsay, E. A. Del Rio Chanona, M. Mowbray

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Forager: a lightweight testbed for continual learning with partial observability in RL

Reinforcement Learning Journal (RLJ) · 2026

Steven Tang, X. Xiong, Anna Hakhverdyan, Andrew Patterson, Jacob Adkins, Jiamin He, Esraa Elelimy, Parham M. Panahi, Martha White, Adam White.

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Forager: a lightweight testbed for continual learning with partial observability in RL

Reinforcement Learning Journal (RLJ) · 2026

Steven Tang, X. Xiong, Anna Hakhverdyan, Andrew Patterson, Jacob Adkins, Jiamin He, Esraa Elelimy, Parham M. Panahi, Martha White, Adam White.

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An Analysis of Action-Value Temporal-Difference Methods That Learn State Values

Reinforcement Learning Conference (RLC) · 2025

Brett Daley, Prabhat Nagarajan, Martha White, Marlos C. Machado

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Deep Reinforcement Learning with Gradient Eligibility Traces

Reinforcement Learning Conference (RLC) · 2025

Esraa Elelimy, Brett Daley, Andy Patterson, Marlos C. Machado, Adam White, Martha White

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Rethinking the Foundations for Continual Reinforcement Learning

Reinforcement Learning Conference (RLC) · 2025

Esraa Elelimy, David Szepesvari, Martha White, Michael Bowling

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Investigating the Utility of Mirror Descent in Off-policy Actor-Critic.

Reinforcement Learning Conference (RLC) · 2025

Samuel Neumann, Jiamin He, Adam White, Martha White

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Value Bonuses using Ensemble Errors for Exploration in Reinforcement Learning

Reinforcement Learning Conference (RLC) · 2025

Abdul Wahab, Raksha Kumaraswamy, Martha White

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Position: Lifetime tuning is incompatible with continual reinforcement learning

International Conference on Machine Learning (ICML) · 2025

Golnaz Mesbahi, Parham M. Panahi, Olya Mastikhina, Steven Tang, Martha White, Adam White

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q-exponential family for policy optimization

International Conference on Learning Representations (ICLR) · 2025

Lingwei Zhu, Haseeb Shah, Han Wang, Y. Nagai, Martha White

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Is Okham’s razor losing its edge? New perspectives on the principle of model parsimony.

Proceedings of the National Academy of Sciences (PNAS) · 2024

M. Dubova, S. Chandramouli, G. Gigerenzer, P. Grunwald, W.Holmes, T. Lombrozo, M. Marelli, S. Musslick, B. Nicenboim, L. N. Ross, R. Shiffrin, M. White, E-J. Wagenmakers, P-C. Burkner, S. Sloman

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Data-Efficient Policy Evaluation Through Behavior Policy Search

Journal of Machine Learning Research (JMLR) · 2024

Josiah Hanna, Yash Chandak, Philip Thomas, Martha White, Peter Stone, Scott Niekum

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Goal-Space Planning with Subgoal Models

Journal of Machine Learning Research (JMLR) · 2024

Chunlok Lo, Kevin Roice, Parham Mohammad Panahi, Scott Jordan, Adam White, Gabor Mihucz, Farzane Aminmansour, Martha White

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Empirical Design in Reinforcement Learning

Journal of Machine Learning Research (JMLR) · 2024

Andrew Patterson, Samuel Neumann, Martha White, Adam White

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The Cross-environment Hyperparameter Setting Benchmark for Reinforcement Learning

Reinforcement Learning Conference (RLC) · 2024

Andrew Patterson, Samuel Neumann, Raksha Kumaraswamy, Adam White, Martha White

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Investigating the Interplay of Prioritized Replay and Generalization

Reinforcement Learning Conference (RLC) · 2024

Parham Panahi, Andrew Patterson, Martha White, Adam White

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Demystifying the Recency Heuristic in Temporal-Difference Learning

Reinforcement Learning Conference (RLC) · 2024

Brett Daley, Marlos Machado, Martha White

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Multistep Predecessor Models and Mitigating Errors due to Hallucinated Value in Dyna-Style Planning

Journal of AI Research (JAIR) · 2024

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

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Compound Returns Reduce Variance in Reinforcement Learning

International Conference on Machine Learning (ICML) · 2024

Brett Daley, Martha White, Marlos Machado

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Position Paper: Limitations of and Alternatives to Benchmarking in Reinforcement Learning Research

International Conference on Machine Learning (ICML) · 2024

Scott M. Jordan, Bruno Castro da Silva, Adam White, Martha White, Philip S. Thomas

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Offline Reinforcement Learning via Tsallis Regularization

Transactions on Machine Learning Research (TMLR) · 2024

Lingwei Zhu, Matthew Schlegel, Han Wang, Martha White

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Real-time recurrent learning using trace units in reinforcement learning

Advances in Neural Information Processing Systems (Neurips) · 2024

Elelimy, Esraa, White, Adam, Bowling, Michael, White, Martha

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Investigating the Properties of Neural Network Representations in Reinforcement Learning

Artificial Intelligence Journal (AIJ) · 2023

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

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GVFs in the Real World: Making Predictions Online for Water Treatment

Machine Learning (MLJ) · 2023

Kamran Janjua, Haseeb Shah, Martha White, Erfan Miahi, Marlos Machado, Adam White

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General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence

Advances in Neural Information Processing Systems (NeurIPS) · 2023

Lingwei Zhu, Zheng Chen, Matthew Schlegel, Martha White

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Resmax: An Alternative Soft-Greedy Operator for Reinforcement Learning

Transactions on Machine Learning Research (TMLR) · 2023

Erfan Miahi, Revan MacQueen, Alex Ayoub, Abbas Masoumzadeh, Martha White

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Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks

Journal of Machine Learning Research (JMLR) · 2023

Khurram Javed, Haseeb Shah, Richard Sutton, Martha White

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Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning

International Conference on Machine Learning (ICML) · 2023

Brett Daley, Martha White, Chris Amato, Marlos Machado

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Measuring and Mitigating Interference in Reinforcement Learning

Conference on Lifelong Learning Agents (CoLLAs) · 2023

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

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

Journal of Artificial Intelligence Research · 2023

Vincent Liu, James Wright, Martha White

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Off-Policy Actor-Critic with Emphatic Weightings

Journal of Machine Learning Research (JMLR) · 2023

Eric Graves, Ehsan Imani, Raksha Kumaraswamy, Martha White

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Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement

International Conference on Representation Learning (ICLR) · 2023

Samuel Neumann, Sungsu Lim, Ajin George Joseph, Yangchen Pan, Adam White, Martha White

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The In-Sample Softmax for Offline Reinforcement Learning

International Conference on Representation Learning (ICLR) · 2023

Chenjun Xiao, Han Wang, Yangchen Pan, Adam White, Martha White

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

International Conference on AI and Statistics (AISTATS) · 2023

Vincent Liu, Yash Chandak, Phillip Thomas, Martha White

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Representation Alignment in Neural Networks

Transactions on Machine Learning Research (TMLR) · 2022

Ehsan Imani, Wei Hu, Martha White

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Robust Losses for Learning Value Functions

Transactions on Pattern Analysis and Machine Learning (TPAMI) · 2022

Andrew Patterson, Victor Liao, Martha White

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

Journal of Machine Learning Research (JMLR) · 2022

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

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No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL

Transactions on Machine Learning Research (TMLR) · 2022

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

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Understanding and Mitigating the Limitations of Prioritized Replay

Uncertainty in AI (UAI) · 2022

Jincheng Mei, Yangchen Pan, Amir-massoud Farahmand, Hengshuai Yao, Martha White

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A Temporal-Difference Approach to Policy Gradient Estimation

International Conference on Machine Learning (ICML) · 2022

Samuele Tosatto, Andrew Patterson, Martha White, A. Rupam Mahmood

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

Journal of Machine Learning Research (JMLR) · 2022

Andrew Patterson, Adam White, Martha White

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An Alternate Policy Gradient Estimator for Softmax Policies

International Conference on on Artificial Intelligence and Statistics (AISTATS) · 2022

Shivam Garg, Yangchen Pan, Martha White, A. Rupam Mahmood

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

International Conference on Learning Representations (ICLR) · 2022

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

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Sim2Real in Robotics and Automation: Applications and Challenges

IEEE Transactions on Automation Science and Engineering · 2021

S. Hofer, K. Bekris, A. Handa, J.C. Gamboa, M. Mozifian, F. Golemo, C. Atkeson, D. Fox, K. Goldberg, J. Leonard, C, Karen Liu, J. Peters, S. Song, P. Welinder, Peter, M. White

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Continual Auxiliary Task Learning

Advances in Neural Information Processing Systems (NeurIPS) · 2021

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

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Structural Credit Assignment in Neural Networks using Reinforcement Learning

Advances in Neural Information Processing Systems (NeurIPS) · 2021

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

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Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online

International Conference on Learning Representations (ICLR) · 2021

Yangchen Pan, Kirby Banman, Martha White

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General Value Function Networks

Journal of AI Research (JAIR) · 2021

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

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An implicit function learning approach for parametric modal regression

Advances in Neural Information Processing Systems (NeurIPS) · 2020

Yancghen Pan, Ehsan Imani, Martha White

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Towards Safe Policy Improvement for Non-Stationary MDPs

Advances in Neural Information Processing Systems (NeurIPS) · 2020

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

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Adapting Behaviour via Intrinsic Reward: A Survey and Empirical Study

Journal of AI Research (JAIR) · 2020

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

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Gradient Temporal-Difference Learning with Regularized Corrections

International Conference on Machine Learning (ICML) · 2020

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

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Selective Dyna-style Planning Under Limited Model Capacity

International Conference on Machine Learning (ICML) · 2020

Zaheer Abbas, Sam Sokota, Erin Talvitie, Martha White

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Optimizing for the Future in Non-Stationary MDPs

International Conference on Machine Learning (ICML) · 2020

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

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Training Recurrent Neural Networks Online by Learning Explicit State Variables

International Conference on Learning Representations (ICLR) · 2020

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

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Maxmin Q-learning: Controlling the Estimation Bias of Q-learning

International Conference on Learning Representations (ICLR) · 2020

Qingfeng Lan, Yangchen Pan, Alona Fyshe, Martha White

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Maximizing Information Gain in Partially Observable Environments via Prediction Rewards

International Conference on Autonomous Agents and Multi-agent Systems (AAMAS) · 2020

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

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Meta-Learning Representations for Continual Learning

Advances in Neural Information Processing Systems (NeurIPS) · 2019

Khurram Javed, Martha White

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Importance Resampling for Off-policy Prediction

Advances in Neural Information Processing Systems (NeurIPS) · 2019

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

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Learning Macroscopic Brain Connectomes via Group-Sparse Factorization

Advances in Neural Information Processing Systems (NeurIPS) · 2019

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

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Planning with Expectation Models

International Joint Conference on Artificial Intelligence (IJCAI) · 2019

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

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Hill Climbing on Value Estimates for Search-control in Dyna

International Joint Conference on Artificial Intelligence (IJCAI) · 2019

Yangchen Pan, Hengshuai Yao, Amir-massoud Farahmand, Martha White

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Two-Timescale Networks for Nonlinear Value Function Approximation

International Conference on Learning Representations (ICLR) · 2019

Wesley Chung, Somjit Nath, Ajin Joseph, Martha White

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The Utility of Sparse Representations for Control in Reinforcement Learning

AAAI Conference on Artificial Intelligence · 2019

Vincent Liu, Raksha Kumaraswamy, Lei Le, Martha White

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Meta-descent for online, continual prediction

AAAI Conference on Artificial Intelligence · 2019

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

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An Off-policy Policy Gradient Theorem Using Emphatic Weightings

Advances in Neural Information Processing Systems (NIPS) · 2018

Ehsan Imani, Eric Graves, Martha White

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Supervised autoencoders: Improving generalization performance with unsupervised regularizers

Advances in Neural Information Processing Systems (NIPS) · 2018

Lei Le, Andrew Patterson, Martha White

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Context-dependent upper-confidence bounds for directed exploration

Advances in Neural Information Processing Systems (NIPS) · 2018

Raksha Kumaraswamy, Matthew Schlegel, Adam White, Martha White

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Improving Regression Performance with Distributional Losses

International Conference on Machine Learning (ICML) · 2018

Ehsan Imani, Martha White

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Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control

International Conference on Machine Learning (ICML) · 2018

Yangchen Pan, Amir-massoud Farahmand, Martha White, Saleh Nabi, Piyush Grover, Daniel Nikovski

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Organizing experience: a deeper look at replay mechanisms for sample-based planning in continuous state domains

International Joint Conference on Artificial Intelligence (IJCAI) · 2018

Yangchen Pan, Muhammad Zaheer, Adam White, Andrew Patterson, Martha White

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High-confidence error estimates for learned value functions

Uncertainty in Artificial Intelligence (UAI) · 2018

Touqir Sajed, Wesley Chung, Martha White

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Comparing Direct and Indirect Temporal-Difference Methods for Estimating the Variance of the Return

Uncertainty in Artificial Intelligence (UAI) · 2018

Craig Sherstan, Dylan Ashley, Brendan Bennet, Kenny Young, Adam White, Martha White, Richard Sutton

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Multi-view Matrix Factorization for Linear Dynamical System Estimation

Advances in Neural Information Processing Systems (NIPS) · 2017

Mahdi Karami, Martha White, Dale Schuurmans, Csaba Szepesvari

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Unifying task specification in reinforcement learning

International Conference on Machine Learning (ICML) · 2017

Martha White

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Adapting kernel representations online using submodular maximization

International Conference on Machine Learning (ICML) · 2017

Matthew Schlegel, Yangchen Pan, Martha White

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Effective sketching methods for value function approximation

Uncertainty in Artificial Intelligence (UAI) · 2017

Yangchen Pan, Erfan Sadeqi Azer, Martha White

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Learning sparse representations in reinforcement learning with sparse coding

International Joint Conference on Artificial Intelligence (IJCAI) · 2017

Lei Le, Raksha Kumaraswamy, Martha White

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Accelerated Gradient Temporal Difference Learning

AAAI Conference on Artificial Intelligence · 2017

Yangchen Pan, Adam White, Martha White

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Recovering true classifier performance in positive-unlabeled learning

AAAI Conference on Artificial Intelligence · 2017

Shantanu Jain, Martha White, Predrag Radivojac

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

Advances in Neural Information Processing Systems (NIPS) · 2016

Shantanu Jain, Martha White, Predrag Radivojac

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Identifying global optimality for dictionary learning

In submission to JMLR · 2016

Lei Le, Martha White

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Nonparametric semi-supervised learning of class proportions

In submission to JMLR · 2016

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

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Incremental Truncated LSTD

International Joint Conference on Artificial Intelligence (IJCAI) · 2016

Clement Gehring, Yangchen Pan, Martha White

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Investigating practical, linear temporal difference learning

Autonomous Agents and Multi-agent Systems (AAMAS) · 2016

Adam White, Martha White

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

Autonomous Agents and Multi-agent Systems (AAMAS) · 2016

Adam White, Martha White

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

Journal of Machine Learning Research (JMLR) · 2016

Richard S. Sutton, A Rupam Mahmood, Martha White

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Scalable Metric Learning for Co-embedding

ECML PKDD · 2015

Farzaneh Mirzazadeh, Martha White, Andras Gyorgy, Dale Schuurmans

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Optimal Estimation of Multivariate ARMA Models

AAAI Conference on Artificial Intelligence · 2015

Martha White, Junfeng Wen, Michael Bowling, Dale Schuurmans

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Partition Tree Weighting

Data Compression Conference (DCC) · 2013

Joel Veness, Martha White, Michael Bowling, Andras Gyorgy

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Convex Multi-view Subspace Learning

Advances in Neural Information Processing Systems (NIPS) · 2012

Martha White, Yaoliang Yu, Xinhua Zhang, Dale Schuurmans

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Off-Policy Actor-Critic

International Conference on Machine Learning (ICML) · 2012

Thomas Degris, Martha White, Richard S. Sutton

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Generalized Optimal Reverse Prediction

International Conference on Artificial Intelligence and Statistics (AISTATS) · 2012

Martha White, Dale Schuurmans

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

AAAI Conference on Artificial Intelligence (AAAI) · 2011

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

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

Advances in Neural Information Processing Systems (NIPS) · 2010

Martha White, Adam White

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

Advances in Neural Information Processing Systems (NIPS) · 2010

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

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Learning a Value Analysis Tool For Agent Evaluation

International Joint Conference on Artificial Intelligence (IJCAI) · 2009

Martha White, Michael Bowling

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Optimal Reverse Prediction: A Unified Perspective on Supervised, Unsupervised and Semi-supervised Learning

International Conference on Machine Learning (ICML) · 2009

Linli Xu, Martha White, Dale Schuurmans

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