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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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03/10/2023
A General Recipe for the Analysis of Randomized Multi-Armed Bandit Algorithms
In this paper we propose a general methodology to derive regret bounds f...
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02/03/2023
Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits
In the stochastic multi-armed bandit problem, a randomized probability m...
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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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06/09/2022
Globally Optimal Algorithms for Fixed-Budget Best Arm Identification
We consider the fixed-budget best arm identification problem where the g...
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06/07/2022
The Survival Bandit Problem
We study the survival bandit problem, a variant of the multi-armed bandi...
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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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07/23/2021
Finite-time Analysis of Globally Nonstationary Multi-Armed Bandits
We consider nonstationary multi-armed bandit problems where the model pa...
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07/16/2021
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences
Ordinary supervised learning is useful when we have paired training data...
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12/31/2020
Combinatorial Pure Exploration with Full-bandit Feedback and Beyond: Solving Combinatorial Optimization under Uncertainty with Limited Observation
Combinatorial optimization is one of the fundamental research fields tha...
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06/24/2020
Online Dense Subgraph Discovery via Blurred-Graph Feedback
Dense subgraph discovery aims to find a dense component in edge-weighted...
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06/17/2020
Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring
We investigate finite stochastic partial monitoring, which is a general ...
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03/10/2020
Time-varying Gaussian Process Bandit Optimization with Non-constant Evaluation Time
The Gaussian process bandit is a problem in which we want to find a maxi...
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02/13/2020
Adaptive Experimental Design for Efficient Treatment Effect Estimation: Randomized Allocation via Contextual Bandit Algorithm
Many scientific experiments have an interest in the estimation of the av...
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05/31/2019
Uncoupled Regression from Pairwise Comparison Data
Uncoupled regression is the problem to learn a model from unlabeled data...
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03/19/2019
A Note on KL-UCB+ Policy for the Stochastic Bandit
A classic setting of the stochastic K-armed bandit problem is considered...
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02/27/2019
Polynomial-time Algorithms for Combinatorial Pure Exploration with Full-bandit Feedback
We study the problem of stochastic combinatorial pure exploration (CPE),...
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01/31/2019
A Bad Arm Existence Checking Problem
We study a bad arm existing checking problem in which a player's task is...
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01/30/2019
On Possibility and Impossibility of Multiclass Classification with Rejection
We investigate the problem of multiclass classification with rejection, ...
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09/14/2018
Dueling Bandits with Qualitative Feedback
We formulate and study a novel multi-armed bandit problem called the qua...
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09/11/2018
Unsupervised Domain Adaptation Based on Source-guided Discrepancy
Unsupervised domain adaptation is the problem setting where data generat...
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10/17/2017
Good Arm Identification via Bandit Feedback
In this paper, we consider and discuss a new stochastic multi-armed band...
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10/16/2017
Fully adaptive algorithm for pure exploration in linear bandits
We propose the first fully-adaptive algorithm for pure exploration in li...
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05/05/2016
Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm
We study the K-armed dueling bandit problem, a variation of the standard...
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09/30/2015
Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring
Partial monitoring is a general model for sequential learning with limit...
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06/08/2015
Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem
We study the K-armed dueling bandit problem, a variation of the standard...
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06/02/2015
Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays
We discuss a multiple-play multi-armed bandit (MAB) problem in which sev...
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04/22/2015
