First-Order Methods In Optimization (MOS-SIAM Series on Optimization) - Softcover

Amir Beck (author)

Softcover

ISBN 10: 1611974984 ISBN 13: 9781611974980

Publisher: SIAM - Society for Industrial and Applied Mathematics, 2017

Synopsis

The primary goal of this book is to provide a self-contained, comprehensive study of the main ?rst-order methods that are frequently used in solving large-scale problems. First-order methods exploit information on values and gradients/subgradients (but not Hessians) of the functions composing the model under consideration. With the increase in the number of applications that can be modeled as large or even huge-scale optimization problems, there has been a revived interest in using simple methods that require low iteration cost as well as low memory storage.

The author has gathered, reorganized, and synthesized (in a unified manner) many results that are currently scattered throughout the literature, many of which cannot be typically found in optimization books.

First-Order Methods in Optimization offers comprehensive study of first-order methods with the theoretical foundations; provides plentiful examples and illustrations; emphasizes rates of convergence and complexity analysis of the main first-order methods used to solve large-scale problems; and covers both variables and functional decomposition methods.

Edition details

• Publisher: SIAM - Society for Industrial and Applied Mathematics
• Publication date: 2017
• Language: English
• ISBN 10: 1611974984
• ISBN 13: 9781611974980
• Binding: Paperback
• Number of pages: 484