70 citations · 161 across the 37 of their papers we have counts for
5 papers · 1 filter
Rate-optimal Design for Anytime Best Arm Identification
Junpei Komiyama, Kyoungseok Jang, Junya Honda
We consider the best arm identification problem, where the goal is to identify the arm with the highest mean reward from a set of arms under a limited sampling budget. This pro…
Best-of- -- Asymptotic Performance of Test-Time LLM Ensembling
Junpei Komiyama, Daisuke Oba, Masafumi Oyamada
We study best-of- for large language models (LLMs) where the selection is based on majority voting. In particular, we analyze the limit , which we denote as \boinf…
High-dimensional Nonparametric Contextual Bandit Problem
Shogo Iwazaki, Junpei Komiyama, Masaaki Imaizumi
We consider the kernelized contextual bandit problem with a large feature space. This problem involves arms, and the goal of the forecaster is to maximize the cumulative reward…
No-regret incentive-compatible online learning under exact truthfulness with non-myopic experts
Junpei Komiyama, Nishant A. Mehta, Ali Mortazavi
We study an online forecasting setting in which, over rounds, strategic experts each report a forecast to a mechanism, the mechanism selects one forecast, and then the outc…
Data-dependent Bounds with -Optimal Best-of-Both-Worlds Guarantees in Multi-Armed Bandits using Stability-Penalty Matching
Quan Nguyen, Shinji Ito, Junpei Komiyama +1
Existing data-dependent and best-of-both-worlds regret bounds for multi-armed bandits problems have limited adaptivity as they are either data-dependent but not best-of-both-worlds…