Martha White

Investigating the Histogram Loss in Regression JMLR 2026 q-exponential family for policy optimization ICLR 2025 Position: Lifetime tuning is incompatible with continual reinforcement learning ICML 2025 Averaging n-step Returns Reduces Variance in Reinforcement Learning ICML 2024 Data-Efficient Policy Evaluation Through Behavior Policy Search JMLR 2024 Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers NeurIPS 2024 Empirical Design in Reinforcement Learning JMLR 2024 Goal-Space Planning with Subgoal Models JMLR 2024 Position: Benchmarking is Limited in Reinforcement Learning Research ICML 2024 Real-Time Recurrent Learning using Trace Units in Reinforcement Learning NeurIPS 2024 Asymptotically Unbiased Off-Policy Policy Evaluation when Reusing Old Data in Nonstationary Environments AISTATS 2023 General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence NeurIPS 2023 Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement ICLR 2023 Off-Policy Actor-Critic with Emphatic Weightings JMLR 2023 Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks JMLR 2023 The In-Sample Softmax for Offline Reinforcement Learning ICLR 2023 Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning ICML 2023 A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning JMLR 2022 An Alternate Policy Gradient Estimator for Softmax Policies AISTATS 2022 A Temporal-Difference Approach to Policy Gradient Estimation ICML 2022 Greedification Operators for Policy Optimization: Investigating Forward and Reverse KL Divergences JMLR 2022 Resonance in Weight Space: Covariate Shift Can Drive Divergence of SGD with Momentum ICLR 2022 Understanding and mitigating the limitations of prioritized experience replay UAI 2022 Continual Auxiliary Task Learning NeurIPS 2021 Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online ICLR 2021 Structural Credit Assignment in Neural Networks using Reinforcement Learning NeurIPS 2021 An implicit function learning approach for parametric modal regression NeurIPS 2020 From Language to Language-ish: How Brain-Like is an LSTM’s Representation of Nonsensical Language Stimuli? EMNLP 2020 Gradient Temporal-Difference Learning with Regularized Corrections ICML 2020 Maxmin Q-learning: Controlling the Estimation Bias of Q-learning ICLR 2020 Optimizing for the Future in Non-Stationary MDPs ICML 2020 Selective Dyna-Style Planning Under Limited Model Capacity ICML 2020 Towards Safe Policy Improvement for Non-Stationary MDPs NeurIPS 2020 Training Recurrent Neural Networks Online by Learning Explicit State Variables ICLR 2020 Hill Climbing on Value Estimates for Search-control in Dyna IJCAI 2019 Importance Resampling for Off-policy Prediction NeurIPS 2019 Learning Macroscopic Brain Connectomes via Group-Sparse Factorization NeurIPS 2019 Meta-Descent for Online, Continual Prediction AAAI 2019 Meta-Learning Representations for Continual Learning NeurIPS 2019 Planning with Expectation Models IJCAI 2019 The Utility of Sparse Representations for Control in Reinforcement Learning AAAI 2019 Two-Timescale Networks for Nonlinear Value Function Approximation ICLR 2019 An Off-policy Policy Gradient Theorem Using Emphatic Weightings NeurIPS 2018 Context-dependent upper-confidence bounds for directed exploration NeurIPS 2018 Improving Regression Performance with Distributional Losses ICML 2018 Organizing Experience: a Deeper Look at Replay Mechanisms for Sample-Based Planning in Continuous State Domains IJCAI 2018 Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control ICML 2018 Supervised autoencoders: Improving generalization performance with unsupervised regularizers NeurIPS 2018 Adapting Kernel Representations Online Using Submodular Maximization ICML 2017 Learning Sparse Representations in Reinforcement Learning with Sparse Coding IJCAI 2017 Multi-view Matrix Factorization for Linear Dynamical System Estimation NeurIPS 2017 Unifying Task Specification in Reinforcement Learning ICML 2017 An Emphatic Approach to the Problem of Off-policy Temporal-Difference Learning JMLR 2016 Estimating the class prior and posterior from noisy positives and unlabeled data NeurIPS 2016 Incremental Truncated LSTD IJCAI 2016 Convex Multi-view Subspace Learning NeurIPS 2012 Generalized Optimal Reverse Prediction AISTATS 2012 Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains NeurIPS 2010 Relaxed Clipping: A Global Training Method for Robust Regression and Classification NeurIPS 2010