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← Authors

Adam White

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

Achievements

Jump to papers ↓
+15 more ↓ 🌍 Conference Polyglot (6) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🏃 Academic Marathon (16)
🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (13) 🤝 Dynamic Duo (16) 🧬 Topic Evolution 🏆 Grand Slam 🌱 Topic Pioneer 🔬 Deep Specialist (10) 🏆 Keyword Champion (2) 🚀 Conference Pioneer 🗃️ Keyword Collector (75) ⚡ Prolific Year (7) 🔥 Unstoppable (8) 💎 Century Club (22) 📈 Trend Setter

Conferences

ICML (5) NIPS (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)

Keywords

reinforcement learning (7) model-based reinforcement learning (4) off-policy learning (4) temporal difference learning (3) value function approximation (2) state abstraction (2) hyperparameter sensitivity (2) temporal abstraction (2) experience replay (2) function approximation (2) continuous state (2) hypothesis testing (1) software framework (1) value function (1) stability analysis (1) policy evaluation (1) continual learning (1) performance evaluation (1) deep learning (1) experimental design (1)

Papers

Position: Lifetime tuning is incompatible with continual reinforcement learning ICML 2025 Position: Benchmarking is Limited in Reinforcement Learning Research ICML 2024 Real-Time Recurrent Learning using Trace Units in Reinforcement Learning NIPS 2024 A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning NIPS 2024 Empirical Design in Reinforcement Learning JMLR 2024 Reward-Respecting Subtasks for Model-Based Reinforcement Learning (Abstract Reprint) AAAI 2024 Goal-Space Planning with Subgoal Models JMLR 2024 Position: Application-Driven Innovation in Machine Learning ICML 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 Learning Expected Emphatic Traces for Deep RL AAAI 2022 A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning JMLR 2022 Continual Auxiliary Task Learning NIPS 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 Planning with Expectation Models IJCAI 2019 Meta-Descent for Online, Continual Prediction AAAI 2019 Organizing Experience: a Deeper Look at Replay Mechanisms for Sample-Based Planning in Continuous State Domains IJCAI 2018 Context-dependent upper-confidence bounds for directed exploration NIPS 2018 Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains NIPS 2010 RL-Glue: Language-Independent Software for Reinforcement-Learning Experiments JMLR 2009