20 citations · 34 across the 7 of their papers we have counts for
7 papers · 1 filter
An Efficient Algorithm for Thresholding Monte Carlo Tree Search
Shoma Nameki, Atsuyoshi Nakamura, Junpei Komiyama +1
We introduce the Thresholding Monte Carlo Tree Search problem, in which, given a tree and a threshold , a player must answer whether the root node value of $\mathc…
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…
Two-stage Algorithm for Fairness-aware Machine Learning
Junpei Komiyama, Hajime Shimao
Algorithmic decision making process now affects many aspects of our lives. Standard tools for machine learning, such as classification and regression, are subject to the bias in da…
Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm
Junpei Komiyama, Junya Honda, Hiroshi Nakagawa
We study the K-armed dueling bandit problem, a variation of the standard stochastic bandit problem where the feedback is limited to relative comparisons of a pair of arms. The hard…