Taking the Human Out of the Loop: A Review of Bayesian Optimization

Abstract

The end products (e.g., recommendation systems, medical analysis tools, real-time game engines, speech recognizers) involves many tunable configuration parameters. These parameters are often specified and hard-coded into the software by various developers or teams. If optimized jointly, these parameters can result in significant improvements.

A Bayesian optimization is a powerful tool for the joint optimization of design choices that is gaining great popularity in recent years. It promises greater automation so as to increase both product quality and human productivity.

This review paper introduces Bayesian optimization, highlights some of its methodological aspects, and showcases a wide range of applications.

Introduction

Problem definition:

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