Junya Honda
36 papers · 2012–2025 · 10 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π§ Keyword Pioneer π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (16) π Conference Polyglot (10)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π
Academic Marathon
(13)
π€
Dynamic Duo
(11)
π
Grand Slam
π¬
Deep Specialist
(15)
π₯
Unstoppable
(12)
π
Conference Pioneer
β‘
Prolific Year
(6)
ποΈ
Keyword Collector
(107)
π
Trend Setter
π
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
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