First-Order Methods in Optimization

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  • First-Order Methods in Optimization Book Detail

  • Author : Amir Beck
  • Release Date : 2017-10-02
  • Publisher : SIAM
  • Genre : Mathematics
  • Pages : 476
  • ISBN 13 : 1611974984
  • File Size : 29,29 MB

First-Order Methods in Optimization by Amir Beck PDF Summary

Book Description: 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.

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