Junpei Komiyama

Junpei Komiyama

Assistant Professor at MBZUAI. Research: Machine Learning, Multi-armed Bandits, Monte Carlo Tree Search, Algorithmic Bias

Fixed Confidence Best Arm Identification in the Bayesian Setting

Published in Advances in Neural Information Processing Systems (NeurIPS), 2024

This paper addresses fixed confidence best arm identification in the Bayesian setting. We provide theoretical analysis and practical algorithms for Bayesian bandit problems, establishing optimal stopping rules and confidence bounds for identifying the best arm with high confidence.

Download paper here

Recommended citation: Jang, K., Komiyama, J., & Yamazaki, K. (2024). “Fixed Confidence Best Arm Identification in the Bayesian Setting.” In Advances in Neural Information Processing Systems (NeurIPS 2024).

Recommended citation: Jang, K., Komiyama, J., & Yamazaki, K. (2024). "Fixed Confidence Best Arm Identification in the Bayesian Setting." In Advances in Neural Information Processing Systems (NeurIPS 2024).
Download Paper