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Martha White

58 papers · 2010–2025 · 9 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (20) 🐝 Cross-Pollinator (14) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (15) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (9) 🌈 Renaissance Researcher (6) 🀝 Dynamic Duo (16) πŸ‘‘ Triple Crown 🧬 Topic Evolution πŸ† Keyword Champion πŸ† Grand Slam 🌱 Topic Pioneer πŸ”¬ Deep Specialist (20) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (10) ⚑ Prolific Year (8) πŸ—ƒοΈ Keyword Collector (75) πŸ’Ž Century Club (58) ❓ The Questioner

Conferences

NIPS (18) ICML (12) ICLR (8) JMLR (8) IJCAI (5) AISTATS (3) AAAI (2) EMNLP (1) UAI (1)

Top co-authors

Adam White (16) Yangchen Pan (12) Matthew Schlegel (7) Andrew Patterson (7) Raksha Kumaraswamy (5) Amir-massoud Farahmand (4) Dale Schuurmans (4) Lei Le (4) Yash Chandak (4) Ehsan Imani (4)

Research topics

Reinforcement Learning (1)

Keywords

reinforcement learning (17) off-policy learning (8) policy gradient (6) model-based reinforcement learning (5) value function (4) online learning (4) sample efficiency (4) recurrent neural network (3) policy evaluation (3) continual learning (3) temporal-difference learning (3) neural network (3) continuous state (2) replay buffer (2) temporal difference learning (2) representation learning (2) policy optimization (2) convex optimization (2) function approximation (2) importance sampling (2)

Papers

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