Fr. 91.00

Bayesian Optimization and Data Science

English · Paperback / Softback

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Description

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This volume brings together the main results in the field of Bayesian Optimization (BO), focusing on the last ten years and showing how, on the basic framework, new methods have been specialized to solve emerging problems from machine learning, artificial intelligence, and system optimization. It also analyzes the software resources available for BO and a few selected application areas. Some areas for which new results are shown include constrained optimization, safe optimization, and applied mathematics, specifically BO's use in solving difficult nonlinear mixed integer problems. 
The book will help bring readers to a full understanding of the basic Bayesian Optimization framework and gain an appreciation of its potential for emerging application areas. It will be of particular interest to the data science, computer science, optimization, and engineering communities.

List of contents

1. Automated Machine Learning and Bayesian Optimization.- 2. From Global Optimization to Optimal Learning.- 3. The Surrogate Model.- 4. The Acquisition Function.- 5. Exotic BO.- 6. Software Resources.- 7. Selected Applications.

Summary

This volume brings together the main results in the field of Bayesian Optimization (BO), focusing on the last ten years and showing how, on the basic framework, new methods have been specialized to solve emerging problems from machine learning, artificial intelligence, and system optimization. It also analyzes the software resources available for BO and a few selected application areas. Some areas for which new results are shown include constrained optimization, safe optimization, and applied mathematics, specifically BO's use in solving difficult nonlinear mixed integer problems. 
The book will help bring readers to a full understanding of the basic Bayesian Optimization framework and gain an appreciation of its potential for emerging application areas. It will be of particular interest to the data science, computer science, optimization, and engineering communities.

Product details

Authors Francesc Archetti, Francesco Archetti, Antonio Candelieri
Publisher Springer, Berlin
 
Languages English
Product format Paperback / Softback
Released 01.01.2019
 
EAN 9783030244934
ISBN 978-3-0-3024493-4
No. of pages 126
Dimensions 159 mm x 9 mm x 272 mm
Weight 234 g
Illustrations XIII, 126 p. 52 illus., 39 illus. in color.
Series SpringerBriefs in Optimization
Subjects Natural sciences, medicine, IT, technology > Mathematics > Miscellaneous

Operations Research, C, machine learning, Statistics, Bayesianische Inferenz, Mathematics and Statistics, Management & management techniques, Operations Research, Management Science, Management science, Mathematical & statistical software, Mathematical Software, Computer software, Bayesian Inference

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