Approximation and Optimization Algorithms, Complexity and Applications /

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 high...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Demetriou, Ioannis C. (Editor, http://id.loc.gov/vocabulary/relators/edt), Pardalos, Panos M. (Editor, http://id.loc.gov/vocabulary/relators/edt)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
Edition:1st ed. 2019.
Series:Springer Optimization and Its Applications, 145
Subjects:
Online Access:Full Text via HEAL-Link
Description
Summary: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.
Physical Description:X, 237 p. 56 illus., 27 illus. in color. online resource.
ISBN:9783030127671
ISSN:1931-6828 ;
DOI:10.1007/978-3-030-12767-1