Approximation and Optimization

Algorithms, Complexity and Applications

Ioannis C. Demetriou, Panos M. Pardalos

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English

Springer Nature Switzerland AG
22 May 2019

Differential calculus & equations; Calculus of variations; Numerical analysis; Probability & statistics; Algorithms & data structures

Series: Springer Optimization and Its 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 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.

Edited by: Ioannis C. Demetriou, Panos M. Pardalos
Imprint: Springer Nature Switzerland AG
Country of Publication: Switzerland
Edition: 2019 ed.
Volume: 145
Dimensions: Height: 235mm, Width: 155mm,
Weight: 541g
ISBN: 9783030127664
ISBN 10: 3030127664
Series: Springer Optimization and Its Applications
Pages: 237
Publication Date: 22 May 2019
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

Reviews for Approximation and Optimization: Algorithms, Complexity and Applications

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)