Bayesian Optimization -- Multi-Armed Bandit Problem
This work provides a literature survey and experimental replication for researchers interested in Bayesian Optimization applied to the Multi-Armed Bandit Problem.
This report surveys Bayesian Optimization methods for the Multi-Armed Bandit Problem, specifically focusing on acquisition functions and portfolio strategies. The authors replicate experiments from 'Portfolio Allocation for Bayesian Optimization' and compare their findings to the original paper's results.
In this report, we survey Bayesian Optimization methods focussed on the Multi-Armed Bandit Problem. We take the help of the paper "Portfolio Allocation for Bayesian Optimization". We report a small literature survey on the acquisition functions and the types of portfolio strategies used in papers discussing Bayesian Optimization. We also replicate the experiments and report our findings and compare them to the results in the paper. Code link: https://colab.research.google.com/drive/1GZ14klEDoe3dcBeZKo5l8qqrKf_GmBDn?usp=sharing#scrollTo=XgIBau3O45_V.