TY  - GEN
AU  - Beck, Amir
TI  - First-order methods in optimization
T2  -  / edited by Katya Scheinberg; no.25
SN  - 9781611974980
U1  - 519.6 
PY  - 2017///
CY  - Philadelphia
PB  - SIAM
KW  - Mathematical optimization
KW  - First-order logic
N2  - The primary goal of this book is to provide a self-contained, comprehensive study of the main first-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
ER  -