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05/26/2023
A Mechanism for Sample-Efficient In-Context Learning for Sparse Retrieval Tasks
We study the phenomenon of in-context learning (ICL) exhibited by large ...
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02/07/2023
Leveraging User-Triggered Supervision in Contextual Bandits
We study contextual bandit (CB) problems, where the user can sometimes r...
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06/20/2022
Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality
We revisit the problem of stochastic online learning with feedback graph...
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10/25/2021
The Pareto Frontier of model selection for general Contextual Bandits
Recent progress in model selection raises the question of the fundamenta...
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07/02/2021
Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning
We provide improved gap-dependent regret bounds for reinforcement learni...
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06/16/2020
Corralling Stochastic Bandit Algorithms
We study the problem of corralling stochastic bandit algorithms, that is...
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02/22/2020
Private Stochastic Convex Optimization: Efficient Algorithms for Non-smooth Objectives
In this paper, we revisit the problem of private stochastic convex optim...
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07/29/2019
Bandits with Feedback Graphs and Switching Costs
We study the adversarial multi-armed bandit problem where partial observ...
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11/09/2018
Policy Regret in Repeated Games
The notion of policy regret in online learning is a well defined? perfor...
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08/02/2018
Streaming Kernel PCA with Õ(√(n)) Random Features
We study the statistical and computational aspects of kernel principal c...
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02/22/2017