Strong Convergence of Projected Subgradient Methods for Nonsmooth and Nonstrictly Convex Minimization View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2008-12

AUTHORS

Paul-Emile Maingé

ABSTRACT

In this paper, we establish a strong convergence theorem regarding a regularized variant of the projected subgradient method for nonsmooth, nonstrictly convex minimization in real Hilbert spaces. Only one projection step is needed per iteration and the involved stepsizes are controlled so that the algorithm is of practical interest. To this aim, we develop new techniques of analysis which can be adapted to many other non-Fejérian methods. More... »

PAGES

899-912

References to SciGraph publications

Journal

TITLE

Set-Valued Analysis

ISSUE

7-8

VOLUME

16

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11228-008-0102-z

DOI

http://dx.doi.org/10.1007/s11228-008-0102-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1020109765


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