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Convex optimization in normed spaces...

Peypouquet, Juan.

Convex optimization in normed spacestheory, methods and examples /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Convex optimization in normed spacesby Juan Peypouquet.
Reminder of title:	theory, methods and examples /
Author:	Peypouquet, Juan.
Published:	Cham :Springer International Publishing :2015.
Description:	xiv, 124 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Convex functions.
Online resource:	http://dx.doi.org/10.1007/978-3-319-13710-0
ISBN:	9783319137100 (electronic bk.)

Convex optimization in normed spacestheory, methods and examples /
Peypouquet, Juan.

Convex optimization in normed spacestheory, methods and examples /[electronic resource] :by Juan Peypouquet. - Cham :Springer International Publishing :2015. - xiv, 124 p. :ill., digital ;24 cm. - SpringerBriefs in optimization,2190-8354. - SpringerBriefs in optimization..

Basic Functional Analysis -- Existence of Minimizers -- Convex Analysis and Subdifferential Calculus -- Examples -- Problem-solving Strategies -- Keynote Iterative Methods.

This work is intended to serve as a guide for graduate students and researchers who wish to get acquainted with the main theoretical and practical tools for the numerical minimization of convex functions on Hilbert spaces. Therefore, it contains the main tools that are necessary to conduct independent research on the topic. It is also a concise, easy-to-follow and self-contained textbook, which may be useful for any researcher working on related fields, as well as teachers giving graduate-level courses on the topic. It will contain a thorough revision of the extant literature including both classical and state-of-the-art references.

ISBN: 9783319137100 (electronic bk.)

Standard No.: 10.1007/978-3-319-13710-0doiSubjects--Topical Terms:

191128
Convex functions.

LC Class. No.: QA331.5

Dewey Class. No.: 515.882

Convex optimization in normed spacestheory, methods and examples /
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520 $a This work is intended to serve as a guide for graduate students and researchers who wish to get acquainted with the main theoretical and practical tools for the numerical minimization of convex functions on Hilbert spaces. Therefore, it contains the main tools that are necessary to conduct independent research on the topic. It is also a concise, easy-to-follow and self-contained textbook, which may be useful for any researcher working on related fields, as well as teachers giving graduate-level courses on the topic. It will contain a thorough revision of the extant literature including both classical and state-of-the-art references.
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