Dylan J. Foster
21 papers · 2017–2025 · 4 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (8) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (4) π Cross-Pollinator (11)
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Cross-Pollinator
(11)
πΊοΈ
Taxonomy Completionist
(29)
π¬
Deep Specialist
(11)
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Keyword Champion
(4)
β‘
Prolific Year
(7)
ποΈ
Keyword Collector
(86)
π
Century Club
(21)
β
The Questioner
(2)
Conferences
COLT (13)
NIPS (6)
IJCAI (1)
JMLR (1)
Top co-authors
Keywords
regret bound
(5)
online learning
(5)
reinforcement learning
(4)
interactive decision making
(4)
sample complexity
(4)
statistical learning
(3)
function approximation
(3)
learning theory
(3)
information theory
(2)
sample-efficient learning
(2)
neyman orthogonality
(2)
domain adaptation
(2)
contextual bandit
(2)
stationary point
(2)
oracle complexity
(2)
multi-armed bandit
(2)
excess risk
(2)
in-context learning
(1)
decision making
(1)
logistic regression
(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