Bayesian optimization with application to computer experiments / Tony Pourmohamad, Herbert K.H. Lee.
Pourmohamad, Tony, author.; Lee, Herbert K. H., author.
2021
QA279 .P68 2021
Available Online

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Title Bayesian optimization with application to computer experiments / Tony Pourmohamad, Herbert K.H. Lee.
Author Pourmohamad, Tony, author.
ISBN 9783030824587 (electronic bk.)
3030824586 (electronic bk.)
9783030824570
3030824578
DOI https://doi.org/10.1007/978-3-030-82458-7
Published Cham : Springer, [2021]
Copyright ©2021
Language English
Description 1 online resource : illustrations (chiefly color)
Other Standard Identifiers 10.1007/978-3-030-82458-7 doi
Call Number QA279 .P68 2021
Dewey Decimal Classification 519.5
Summary This book introduces readers to Bayesian optimization, highlighting advances in the field and showcasing its successful applications to computer experiments. R code is available as online supplementary material for most included examples, so that readers can better comprehend and reproduce methods. Compact and accessible, the volume is broken down into four chapters. Chapter 1 introduces the reader to the topic of computer experiments; it includes a variety of examples across many industries. Chapter 2 focuses on the task of surrogate model building and contains a mix of several different surrogate models that are used in the computer modeling and machine learning communities. Chapter 3 introduces the core concepts of Bayesian optimization and discusses unconstrained optimization. Chapter 4 moves on to constrained optimization, and showcases some of the most novel methods found in the field. This will be a useful companion to researchers and practitioners working with computer experiments and computer modeling. Additionally, readers with a background in machine learning but minimal background in computer experiments will find this book an interesting case study of the applicability of Bayesian optimization outside the realm of machine learning.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Digital File Characteristics text file
PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed October 13, 2021).
Added Author Lee, Herbert K. H., author.
Series SpringerBriefs in statistics.
Available in Other Form Bayesian optimization with application to computer experiments.
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
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1. Computer experiments
2. Surrogate models
3. Unconstrained optimization
4. Constrained optimization.

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