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Dylan J. Foster

21 papers · 2017–2025 · 4 conferences · across top CS/AI conferences

Achievements

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+8 more ↓ πŸƒ Academic Marathon (8) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (4) 🐝 Cross-Pollinator (11)
🐝 Cross-Pollinator (11) πŸ—ΊοΈ Taxonomy Completionist (29) πŸ”¬ Deep Specialist (11) πŸ† Keyword Champion (4) ⚑ Prolific Year (7) πŸ—ƒοΈ Keyword Collector (86) πŸ’Ž Century Club (21) ❓ The Questioner (2)

Conferences

COLT (13) NIPS (6) IJCAI (1) JMLR (1)

Papers

Necessary and Sufficient Oracles: Toward a Computational Taxonomy for Reinforcement Learning COLT 2025 Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier: Autoregressive and Imitation Learning under Misspecification (extended abstract) COLT 2025 Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability NIPS 2024 Can large language models explore in-context? NIPS 2024 Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning NIPS 2024 Reinforcement Learning Under Latent Dynamics: Toward Statistical and Algorithmic Modularity NIPS 2024 The Power of Resets in Online Reinforcement Learning NIPS 2024 Online Estimation via Offline Estimation: An Information-Theoretic Framework NIPS 2024 Contextual Bandits with Packing and Covering Constraints: A Modular Lagrangian Approach via Regression JMLR 2024 On the Complexity of Multi-Agent Decision Making: From Learning in Games to Partial Monitoring COLT 2023 Tight Guarantees for Interactive Decision Making with the Decision-Estimation Coefficient COLT 2023 Instance-Optimality in Interactive Decision Making: Toward a Non-Asymptotic Theory COLT 2023 Statistical Learning with a Nuisance Component (Extended Abstract) IJCAI 2020 Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations COLT 2020 Open Problem: Model Selection for Contextual Bandits COLT 2020 Sum-of-squares meets square loss: Fast rates for agnostic tensor completion COLT 2019 The Complexity of Making the Gradient Small in Stochastic Convex Optimization COLT 2019 Statistical Learning with a Nuisance Component COLT 2019 Logistic Regression: The Importance of Being Improper COLT 2018 Online Learning: Sufficient Statistics and the Burkholder Method COLT 2018 ZigZag: A New Approach to Adaptive Online Learning COLT 2017