Overview
- Presents approximation-related algorithms and their relevant applications
- Contains new approaches and techniques to data-dependent approximation
- Highlights new research results
Part of the book series: Springer Optimization and Its Applications (SOIA, volume 145)
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Table of contents (11 chapters)
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Front Matter
Keywords
About this book
This book focuses on the development of approximation-related algorithms and their relevant applications. Individual contributions are written by leading experts and reflect emerging directions and connections in data approximation and optimization. Chapters discuss state of the art topics with highly relevant applications throughout science, engineering, technology and social sciences. Academics, researchers, data science practitioners, business analysts, social sciences investigators and graduate students will find the number of illustrations, applications, and examples provided useful.
This volume is based on the conference Approximation and Optimization: Algorithms, Complexity, and Applications, which was held in the National and Kapodistrian University of Athens, Greece, June 29–30, 2017. The mix of survey and research content includes topics in approximations to discrete noisy data; binary sequences; design of networks and energy systems; fuzzy control; large scale optimization; noisy data; data-dependent approximation; networked control systems; machine learning ; optimal design; no free lunch theorem; non-linearly constrained optimization; spectroscopy.
Reviews
“This book would be suitable as a textbook at any level, but it could be of interest to researchers currently working on optimization problems.” (MAA Reviews, February 24, 2020)
Editors and Affiliations
Bibliographic Information
Book Title: Approximation and Optimization
Book Subtitle: Algorithms, Complexity and Applications
Editors: Ioannis C. Demetriou, Panos M. Pardalos
Series Title: Springer Optimization and Its Applications
DOI: https://doi.org/10.1007/978-3-030-12767-1
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-12766-4Published: 22 May 2019
Softcover ISBN: 978-3-030-12769-5Published: 14 August 2020
eBook ISBN: 978-3-030-12767-1Published: 10 May 2019
Series ISSN: 1931-6828
Series E-ISSN: 1931-6836
Edition Number: 1
Number of Pages: X, 237
Number of Illustrations: 29 b/w illustrations, 27 illustrations in colour
Topics: Approximations and Expansions, Calculus of Variations and Optimal Control; Optimization, Algorithms, Numerical Analysis, Probability Theory and Stochastic Processes