1 citations · 1 across the 7 of their papers we have counts for
7 papers
Minimax and Bayes Optimal Adaptive Experimental Design for Treatment Choice
Masahiro Kato
We consider an adaptive experiment for treatment choice and design a minimax and Bayes optimal adaptive experiment with respect to regret. Given binary treatments, the experimenter…
Minimax and Bayes Optimal Best-Arm Identification
Masahiro Kato
This study investigates minimax and Bayes optimal strategies for fixed-budget best-arm identification. We consider an adaptive procedure consisting of a sampling phase followed by…
Minimax Optimal Simple Regret in Two-Armed Best-Arm Identification
Masahiro Kato
This study investigates an asymptotically minimax optimal algorithm in the two-armed fixed-budget best-arm identification (BAI) problem. Given two treatment arms, the objective is…
Generalized Neyman Allocation for Locally Minimax Optimal Best-Arm Identification
Masahiro Kato
This study investigates an asymptotically locally minimax optimal algorithm for fixed-budget best-arm identification (BAI). We propose the Generalized Neyman Allocation (GNA) algor…
Adaptive Experimental Design for Policy Learning
Masahiro Kato, Kyohei Okumura, Takuya Ishihara +1
This study investigates the contextual best arm identification (BAI) problem, aiming to design an adaptive experiment to identify the best treatment arm conditioned on contextual i…
Locally Optimal Fixed-Budget Best Arm Identification in Two-Armed Gaussian Bandits with Unknown Variances
Masahiro Kato
We address the problem of best arm identification (BAI) with a fixed budget for two-armed Gaussian bandits. In BAI, given multiple arms, we aim to find the best arm, an arm with th…
Worst-Case Optimal Multi-Armed Gaussian Best Arm Identification with a Fixed Budget
Masahiro Kato
This study investigates the experimental design problem for identifying the arm with the highest expected outcome, referred to as best arm identification (BAI). In our experiments,…