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08/15/2023
High-Probability Risk Bounds via Sequential Predictors
Online learning methods yield sequential regret bounds under minimal ass...
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07/03/2023
Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts
We investigate online classification with paid stochastic experts. Here,...
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05/30/2023
Delayed Bandits: When Do Intermediate Observations Help?
We study a K-armed bandit with delayed feedback and intermediate observa...
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05/15/2023
A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs
We derive a new analysis of Follow The Regularized Leader (FTRL) for onl...
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10/09/2022
Learning on the Edge: Online Learning with Stochastic Feedback Graphs
The framework of feedback graphs is a generalization of sequential decis...
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06/06/2022
A Regret-Variance Trade-Off in Online Learning
We consider prediction with expert advice for strongly convex and bounde...
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06/01/2022
A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs
We consider online learning with feedback graphs, a sequential decision-...
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11/02/2021
Nonstochastic Bandits and Experts with Arm-Dependent Delays
We study nonstochastic bandits and experts in a delayed setting where de...
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06/07/2021
Beyond Bandit Feedback in Online Multiclass Classification
We study the problem of online multiclass classification in a setting wh...
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02/15/2021
Distributed Online Learning for Joint Regret with Communication Constraints
In this paper we consider a distributed online learning setting for jo...
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02/12/2021
MetaGrad: Adaptation using Multiple Learning Rates in Online Learning
We provide a new adaptive method for online convex optimization, MetaGra...
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07/24/2020
Exploiting the Surrogate Gap in Online Multiclass Classification
We present Gaptron, a randomized first-order algorithm for online multic...
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07/16/2020
Comparator-adaptive Convex Bandits
We study bandit convex optimization methods that adapt to the norm of th...
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02/21/2018