Strong convergence of a proximal-based method for convex optimization

Vadim Azhmyakov and Werner H. Schmidt

Mathematical Methods of Operations Research, 2003, vol. 57, issue 3, 393-407

Abstract: In this work we study a proximal-like method for the problem of convex minimization in Hilbert spaces. Using the classical proximal mapping, we construct a new stable iterative procedure. The strong convergence of obtained sequences to the normal solution of the optimization problem is proved. Some results of this paper are extended for uniformly convex Banach spaces. Copyright Springer-Verlag Berlin Heidelberg 2003

Keywords: Key words: Convex optimization; proximal point method; strong convergence; nonexpansive mappings (search for similar items in EconPapers)
Date: 2003
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Persistent link: https://EconPapers.repec.org/RePEc:spr:mathme:v:57:y:2003:i:3:p:393-407

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DOI: 10.1007/s001860200261

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