70 citations · 161 across the 37 of their papers we have counts for
5 papers · 1 filter
Rate-optimal Bayesian Simple Regret in Best Arm Identification
Junpei Komiyama, Kaito Ariu, Masahiro Kato +1
We consider best arm identification in the multi-armed bandit problem. Assuming certain continuity conditions of the prior, we characterize the rate of the Bayesian simple regret.…
Deviation-Based Learning: Training Recommender Systems Using Informed User Choice
Junpei Komiyama, Shunya Noda
This paper proposes a new approach to training recommender systems called deviation-based learning. The recommender and rational users have different knowledge. The recommender lea…
Policy Choice and Best Arm Identification: Asymptotic Analysis of Exploration Sampling
Kaito Ariu, Masahiro Kato, Junpei Komiyama +2
We consider the "policy choice" problem -- otherwise known as best arm identification in the bandit literature -- proposed by Kasy and Sautmann (2021) for adaptive experimental des…
Finite-time Analysis of Globally Nonstationary Multi-Armed Bandits
Junpei Komiyama, Edouard Fouché, Junya Honda
We consider nonstationary multi-armed bandit problems where the model parameters of the arms change over time. We introduce the adaptive resetting bandit (ADR-bandit), a bandit alg…
Controlling False Discovery Rates under Cross-Sectional Correlations
Junpei Komiyama, Masaya Abe, Kei Nakagawa +1
We consider controlling the false discovery rate for testing many time series with an unknown cross-sectional correlation structure. Given a large number of hypotheses, false and m…