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Tom Zahavy

23 papers · 2016–2025 · 7 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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+10 more ↓ πŸ—ΊοΈ Taxonomy Completionist (37) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Sprint πŸŒ‰ Interdisciplinary Bridge Β· Silver 🐣 Hot Topic Early Bird
πŸ† Grand Slam πŸ† Keyword Champion (4) 🧭 Keyword Pioneer πŸ‘‘ Triple Crown 🧬 Topic Evolution πŸ”¬ Deep Specialist (10) πŸ’Ž Century Club Β· Bronze πŸ—ƒοΈ Keyword Collector (111) πŸ“ˆ Trend Setter ⚑ Prolific Year Β· Productive

Venues

NeurIPS (8) ICLR (5) ICML (5) AAAI (2) ALT (1) MLHC (1) UAI (1)

Top co-authors

Satinder P. Singh (6) Satinder Singh (6) Sebastian Flennerhag (5) Shie Mannor (5) Zhongwen Xu (4) Vivek Veeriah (4) Daniel J Mankowitz (4) Hado P van Hasselt (3) Brendan O'Donoghue (3) David Silver (3)

Research topics

Reinforcement Learning (16) Methods (16) Machine Learning (13) Artificial Intelligence (12) Core AI (11) Learning Types Β· Machine Learning (9) Deep Learning (6) Optimization & Theory (6) Learning Types Β· Deep Learning (5) Applications (4) Mathematics & Optimization (2) Core Methods (2) Learning Paradigms Β· Machine Learning (2) Learning Paradigms Β· Artificial Intelligence (2) Optimization (2)

Keywords

reinforcement learning (6) apprenticeship learning (4) deep reinforcement learning (3) deep q-network (3) representation learning (2) off-policy learning (2) hierarchical reinforcement learning (2) constrained mdp (2) markov decision process (2) policy optimization (2) atari game (2) fenchel duality (1) feature learning (1) unsupervised pretraining (1) convex optimization (1) black-box optimization (1) temporal difference learning (1) imitation learning (1) neural network optimization (1) in-context learning (1)

Papers

Evaluating In Silico Creativity: An Expert Review of AI Chess Compositions NeurIPS 2025 Mastering Board Games by External and Internal Planning with Language Models ICML 2025 Discovering Evolution Strategies via Meta-Black-Box Optimization ICLR 2023 Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality ICLR 2023 Optimistic Meta-Gradients NeurIPS 2023 ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs ICML 2023 Bootstrapped Meta-Learning ICLR 2022 Online Apprenticeship Learning AAAI 2022 Palm up: Playing in the Latent Manifold for Unsupervised Pretraining NeurIPS 2022 Balancing Constraints and Rewards with Meta-Gradient D4PG ICLR 2021 Discovering a set of policies for the worst case reward ICLR 2021 Discovery of Options via Meta-Learned Subgoals NeurIPS 2021 Emphatic Algorithms for Deep Reinforcement Learning ICML 2021 Online Limited Memory Neural-Linear Bandits with Likelihood Matching ICML 2021 Reward is enough for convex MDPs NeurIPS 2021 Apprenticeship Learning via Frank-Wolfe AAAI 2020 A Self-Tuning Actor-Critic Algorithm NeurIPS 2020 Learning to Ask Medical Questions using Reinforcement Learning MLHC 2020 Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies ALT 2020 Unknown mixing times in apprenticeship and reinforcement learning UAI 2020 Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning NeurIPS 2018 Shallow Updates for Deep Reinforcement Learning NeurIPS 2017 Graying the black box: Understanding DQNs ICML 2016