Junya Honda

Adaptive Learning Rates with Surrogate Probability for Follow-the-Perturbed-Leader COLT 2026 Learning Periodic Strategies in Blocking Bandits Is as Hard as Bandits with Switching Costs COLT 2026 Geometric Resampling in Nearly Linear Time for Follow-the-Perturbed-Leader with Best-of-Both-Worlds Guarantee in Bandit Problems ICML 2025 Multi-Player Approaches for Dueling Bandits AISTATS 2025 Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds COLT 2024 Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring ICML 2024 Finite-time Analysis of Globally Nonstationary Multi-Armed Bandits JMLR 2024 Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds COLT 2024 Learning with Posterior Sampling for Revenue Management under Time-varying Demand IJCAI 2024 Best-of-Both-Worlds Algorithms for Partial Monitoring ALT 2023 Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems ALT 2023 Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits AISTATS 2023 Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits ICML 2023 Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds NeurIPS 2023 Thompson Exploration with Best Challenger Rule in Best Arm Identification ACML 2023 Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds COLT 2022 Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification NeurIPS 2022 Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs NeurIPS 2022 Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences ICML 2021 Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring NeurIPS 2020 Bandit Algorithms Based on Thompson Sampling for Bounded Reward Distributions ALT 2020 Online Dense Subgraph Discovery via Blurred-Graph Feedback ICML 2020 Dueling Bandits with Qualitative Feedback AAAI 2019 Learning from Positive and Unlabeled Data with a Selection Bias ICLR 2019 On the Calibration of Multiclass Classification with Rejection NeurIPS 2019 Uncoupled Regression from Pairwise Comparison Data NeurIPS 2019 Unsupervised Domain Adaptation Based on Source-Guided Discrepancy AAAI 2019 A fully adaptive algorithm for pure exploration in linear bandits AISTATS 2018 Nonconvex Optimization for Regression with Fairness Constraints ICML 2018 Normal Bandits of Unknown Means and Variances JMLR 2018 Position-based Multiple-play Bandit Problem with Unknown Position Bias NeurIPS 2017 Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm ICML 2016 Non-Asymptotic Analysis of a New Bandit Algorithm for Semi-Bounded Rewards JMLR 2015 Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays ICML 2015 Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem COLT 2015 Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring NeurIPS 2015 Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors AISTATS 2014 Stochastic Bandit Based on Empirical Moments AISTATS 2012