First-Order Methods In Optimization - Brossura

Amir Beck (author)

Brossura

ISBN 10: 1611974984 ISBN 13: 9781611974980

Casa editrice: SIAM - Society for Industrial and Applied Mathematics, 2017

Riassunto

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.

Dettagli dell?edizione

• Editore: SIAM - Society for Industrial and Applied Mathematics
• Data di pubblicazione: 2017
• ISBN 10: 1611974984
• ISBN 13: 9781611974980
• Rilegatura: Copertina flessibile
• Lingua: Inglese
• Numero di pagine: 484