← Authors

Junya Honda

36 papers · 2012–2025 · 10 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (10) 🐝 Cross-Pollinator (12) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (16) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (13) 🀝 Dynamic Duo (11) πŸ† Grand Slam πŸ”¬ Deep Specialist (15) πŸ”₯ Unstoppable (12) πŸš€ Conference Pioneer ⚑ Prolific Year (6) πŸ—ƒοΈ Keyword Collector (107) πŸ“ˆ Trend Setter πŸ’Ž Century Club (36)

Conferences

ICML (8) NIPS (8) AISTATS (5) COLT (4) ALT (3) JMLR (3) AAAI (2) ACML (1) ICLR (1) IJCAI (1)

Top co-authors

Masashi Sugiyama (11) Taira Tsuchiya (10) Shinji Ito (10) Junpei Komiyama (8) Jongyeong Lee (4) Hiroshi Nakagawa (4) Akimichi Takemura (3) Liyuan Xu (3) Nontawat Charoenphakdee (2) Akiko Takeda (2)

Keywords

regret bound (20) multi-armed bandit (19) online learning (8) thompson sampling (7) stochastic optimization (6) stochastic bandit (4) online algorithm (4) dueling bandit (3) partial monitoring (3) sample complexity (3) adversarial bandit (2) bandit algorithm (2) optimal algorithm (2) pairwise comparison (2) bayesian inference (2) finite-time analysis (2) posterior sampling (2) best arm identification (2) adversarial corruption (2) stochastic regime (2)

Papers

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