Martha White
58 papers · 2010–2025 · 9 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π£ Hot Topic Early Bird πΊοΈ Taxonomy Completionist (20) π Interdisciplinary Bridge π Conference Polyglot (9)
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Interdisciplinary Bridge
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Conference Polyglot
(9)
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Renaissance Researcher
(6)
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Dynamic Duo
(16)
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Triple Crown
π§¬
Topic Evolution
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Keyword Champion
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Grand Slam
π±
Topic Pioneer
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Deep Specialist
(20)
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Trend Setter
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Conference Pioneer
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Unstoppable
(10)
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Prolific Year
(8)
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Keyword Collector
(75)
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Century Club
(58)
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The Questioner
Conferences
NIPS (18)
ICML (12)
ICLR (8)
JMLR (8)
IJCAI (5)
AISTATS (3)
AAAI (2)
EMNLP (1)
UAI (1)
Top co-authors
Research topics
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 LSTMβs 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