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Adam White

22 papers · 2009–2025 · 6 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+11 more ↓ πŸ—ΊοΈ Taxonomy Completionist (29) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Full πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
πŸ”¬ Deep Specialist (11) πŸ† Grand Slam 🀝 Dynamic Duo (16) 🧬 Topic Evolution πŸ† Keyword Champion (2) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (92) ⚑ Prolific Year Β· Productive πŸ”₯ Unstoppable Β· Bronze πŸ’Ž Century Club Β· Bronze πŸš€ Conference Pioneer

Venues

ICML (5) NeurIPS (5) JMLR (4) AAAI (3) ICLR (3) IJCAI (2)

Top co-authors

Martha White (16) Andrew Patterson (4) Matthew Schlegel (3) Yangchen Pan (3) Parham Mohammad Panahi (2) Chunlok Lo (2) Richard S. Sutton (2) Samuel Neumann (2) Hado van Hasselt (2) Scott M. Jordan (2)

Research topics

Machine Learning (15) Reinforcement Learning (15) Methods (14) Optimization & Theory (11) Learning Types Β· Machine Learning (9) Artificial Intelligence (7) Core AI (7) Deep Learning (5) Applications Β· Reinforcement Learning (5) Learning Types Β· Deep Learning (4) Architectures (2) Computer Science (1) Mathematics & Optimization (1) Applications Β· Computer Science (1) Core Methods (1)

Keywords

reinforcement learning (7) off-policy learning (4) temporal difference learning (4) model-based reinforcement learning (4) function approximation (2) state abstraction (2) online learning (2) recurrent neural network (2) hyperparameter sensitivity (2) experience replay (2) continuous state (2) value function approximation (2) temporal abstraction (2) continual reinforcement learning (1) stability analysis (1) deep learning (1) policy evaluation (1) continual learning (1) policy gradient (1) policy iteration (1)

Papers

Position: Lifetime tuning is incompatible with continual reinforcement learning ICML 2025 A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning NeurIPS 2024 Empirical Design in Reinforcement Learning JMLR 2024 Goal-Space Planning with Subgoal Models JMLR 2024 Position: Application-Driven Innovation in Machine Learning ICML 2024 Position: Benchmarking is Limited in Reinforcement Learning Research ICML 2024 Real-Time Recurrent Learning using Trace Units in Reinforcement Learning NeurIPS 2024 Reward-Respecting Subtasks for Model-Based Reinforcement Learning (Abstract Reprint) AAAI 2024 Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement ICLR 2023 The In-Sample Softmax for Offline Reinforcement Learning ICLR 2023 A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning JMLR 2022 Learning Expected Emphatic Traces for Deep RL AAAI 2022 Continual Auxiliary Task Learning NeurIPS 2021 Emphatic Algorithms for Deep Reinforcement Learning ICML 2021 Gradient Temporal-Difference Learning with Regularized Corrections ICML 2020 Training Recurrent Neural Networks Online by Learning Explicit State Variables ICLR 2020 Meta-Descent for Online, Continual Prediction AAAI 2019 Planning with Expectation Models IJCAI 2019 Context-dependent upper-confidence bounds for directed exploration NeurIPS 2018 Organizing Experience: a Deeper Look at Replay Mechanisms for Sample-Based Planning in Continuous State Domains IJCAI 2018 Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains NeurIPS 2010 RL-Glue: Language-Independent Software for Reinforcement-Learning Experiments JMLR 2009