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05/26/2023
Stability-penalty-adaptive Follow-the-regularized-leader: Sparsity, Game-dependency, and Best-of-both-worlds
Adaptivity to the difficulties of a problem is a key property in sequent...
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02/24/2023
Best-of-Three-Worlds Linear Bandit Algorithm with Variance-Adaptive Regret Bounds
This paper proposes a linear bandit algorithm that is adaptive to enviro...
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07/29/2022
Best-of-Both-Worlds Algorithms for Partial Monitoring
This paper considers the partial monitoring problem with k-actions and d...
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06/14/2022
Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds
This paper considers the multi-armed bandit (MAB) problem and provides a...
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06/02/2022
Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs
This study considers online learning with general directed feedback grap...
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03/15/2022
Online Task Assignment Problems with Reusable Resources
We study online task assignment problem with reusable resources, motivat...
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09/22/2021
On Optimal Robustness to Adversarial Corruption in Online Decision Problems
This paper considers two fundamental sequential decision-making problems...
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01/20/2021
Near-Optimal Regret Bounds for Contextual Combinatorial Semi-Bandits with Linear Payoff Functions
The contextual combinatorial semi-bandit problem with linear payoff func...
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09/05/2019
An Arm-wise Randomization Approach to Combinatorial Linear Semi-bandits
Combinatorial linear semi-bandits (CLS) are widely applicable frameworks...
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06/06/2018
Causal Bandits with Propagating Inference
Bandit is a framework for designing sequential experiments. In each expe...
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05/18/2016