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Nonsmooth optimization and its appli...

Hosseini, Seyedehsomayeh.

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Nonsmooth optimization and its applications

Record Type:	Electronic resources : Monograph/item
Title/Author:	Nonsmooth optimization and its applications/ edited by Seyedehsomayeh Hosseini, Boris S. Mordukhovich, Andre Uschmajew.
other author:	Hosseini, Seyedehsomayeh.
Published:	Cham :Springer International Publishing : : 2019.,
Description:	vii, 149 p. :ill., digital ;24 cm.
[NT 15003449]:	A Collection of Nonsmooth Riemannian Optimization Problems -- An approximate ADMM for solving linearly constrained nonsmooth problems with two blocks of variables -- Tangent and normal cones for low-rank matrices -- Subdifferential enlargements and continuity properties of the VU-decomposition in convex optimization -- Proximal mappings and Moreau envelopes of single-variable convex piecewise cubic functions and multivariable gauge functions -- Newton-like dynamics associated to nonconvex optimization problems.
Contained By:	Springer eBooks
Subject:	Nonsmooth optimization. -
Online resource:	https://doi.org/10.1007/978-3-030-11370-4
ISBN:	9783030113704

Nonsmooth optimization and its applications
Nonsmooth optimization and its applications[electronic resource] /edited by Seyedehsomayeh Hosseini, Boris S. Mordukhovich, Andre Uschmajew. - Cham :Springer International Publishing :2019. - vii, 149 p. :ill., digital ;24 cm. - International series of numerical mathematics,v.1700373-3149 ;. - International series of numerical mathematics ;v.170..

A Collection of Nonsmooth Riemannian Optimization Problems -- An approximate ADMM for solving linearly constrained nonsmooth problems with two blocks of variables -- Tangent and normal cones for low-rank matrices -- Subdifferential enlargements and continuity properties of the VU-decomposition in convex optimization -- Proximal mappings and Moreau envelopes of single-variable convex piecewise cubic functions and multivariable gauge functions -- Newton-like dynamics associated to nonconvex optimization problems.

Since nonsmooth optimization problems arise in a diverse range of real-world applications, the potential impact of efficient methods for solving such problems is undeniable. Even solving difficult smooth problems sometimes requires the use of nonsmooth optimization methods, in order to either reduce the problem's scale or simplify its structure. Accordingly, the field of nonsmooth optimization is an important area of mathematical programming that is based on by now classical concepts of variational analysis and generalized derivatives, and has developed a rich and sophisticated set of mathematical tools at the intersection of theory and practice. This special issue of ISNM is an outcome of the workshop "Nonsmooth Optimization and its Applications," which was held from May 15 to 19, 2017 at the Hausdorff Center for Mathematics, University of Bonn. The six research articles gathered here focus on recent results that highlight different aspects of nonsmooth and variational analysis, optimization methods, their convergence theory and applications.

ISBN: 9783030113704

Standard No.: 10.1007/978-3-030-11370-4doiSubjects--Topical Terms:

709245
Nonsmooth optimization.

LC Class. No.: QA402.5 / .N667 2019

Dewey Class. No.: 519.6

Nonsmooth optimization and its applications
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245 0 0 $a Nonsmooth optimization and its applications $h [electronic resource] / $c edited by Seyedehsomayeh Hosseini, Boris S. Mordukhovich, Andre Uschmajew.
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300 $a vii, 149 p. : $b ill., digital ; $c 24 cm.
490 1 $a International series of numerical mathematics, $x 0373-3149 ; $v v.170
505 0 $a A Collection of Nonsmooth Riemannian Optimization Problems -- An approximate ADMM for solving linearly constrained nonsmooth problems with two blocks of variables -- Tangent and normal cones for low-rank matrices -- Subdifferential enlargements and continuity properties of the VU-decomposition in convex optimization -- Proximal mappings and Moreau envelopes of single-variable convex piecewise cubic functions and multivariable gauge functions -- Newton-like dynamics associated to nonconvex optimization problems.
520 $a Since nonsmooth optimization problems arise in a diverse range of real-world applications, the potential impact of efficient methods for solving such problems is undeniable. Even solving difficult smooth problems sometimes requires the use of nonsmooth optimization methods, in order to either reduce the problem's scale or simplify its structure. Accordingly, the field of nonsmooth optimization is an important area of mathematical programming that is based on by now classical concepts of variational analysis and generalized derivatives, and has developed a rich and sophisticated set of mathematical tools at the intersection of theory and practice. This special issue of ISNM is an outcome of the workshop "Nonsmooth Optimization and its Applications," which was held from May 15 to 19, 2017 at the Hausdorff Center for Mathematics, University of Bonn. The six research articles gathered here focus on recent results that highlight different aspects of nonsmooth and variational analysis, optimization methods, their convergence theory and applications.
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700 1 $a Mordukhovich, Boris S. $3 3338884
700 1 $a Uschmajew, Andre. $3 3386954
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