Bayesian Optimization by Roman Garnett 9781108623551 1108623557

Bayesian Optimization Roman Garnett – Ebook Instant Download/Delivery ISBN(s): 9781108425780, 110842578X, 9781108623551, 1108623557

Product details:

• ISBN 10: 1108623557
• ISBN 13: 9781108623551
• Author: Roman Garnett 

Bayesian optimization is a methodology for optimizing expensive objective functions that has proven success in the sciences, engineering, and beyond. This timely text provides a self-contained and comprehensive introduction to the subject, starting from scratch and carefully developing all the key ideas along the way. This bottom-up approach illuminates unifying themes in the design of Bayesian optimization algorithms and builds a solid theoretical foundation for approaching novel situations. The core of the book is divided into three main parts, covering theoretical and practical aspects of Gaussian process modeling, the Bayesian approach to sequential decision making, and the realization and computation of practical and effective optimization policies. Following this foundational material, the book provides an overview of theoretical convergence results, a survey of notable extensions, a comprehensive history of Bayesian optimization, and an extensive annotated bibliography of applications.

Table contents:

1 Introduction

2 Gaussian Processes

3 Modeling with Gaussian Processes

4 Model Assessment, Selection, and Averaging

5 Decision Theory for Optimization

6 Utility Functions for Optimization

7 Common Bayesian Optimization Policies

8 Computing Policies with Gaussian Processes

9 Implementation

10 Theoretical Analysis

11 Extensions and Related Settings

12 A Brief History of Bayesian Optimization

People also search:

bayesian optimization hyperparameter tuning

optuna bayesian optimization

sklearn bayesian optimization

bayesian optimization tutorial

keras tuner bayesian optimization