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A strongly convergent method for nonsmooth convex minimization in Hilbert spaces

Gespeichert in:

Personen und Körperschaften: Bello Cruz, J. Y. (VerfasserIn), Iusem, A. N. (VerfasserIn)
Titel: A strongly convergent method for nonsmooth convex minimization in Hilbert spaces/ J. Y. Bello Cruz; A. N. Iusem
Format: E-Book
Sprache: Englisch
veröffentlicht:
Rio de Janeiro IMPA 2011
Gesamtaufnahme: Instituto de Matemática Pura e Aplicada: Pré-publicações / A ; 688
Schlagwörter:
Quelle: Verbunddaten SWB
Lizenzfreie Online-Ressourcen
Details
Zusammenfassung: In this paper we propose a strongly convergent variant on the projected subgradient method for constrained convex minimization problems in Hilbert spaces. The advantage of the proposed method is that it converges strongly when the problem has solutions, without additional assumptions. The method also has the following desirable property: the sequence converges to the solution of the problem which lies closest to the initial iterate.
Umfang: Online-Ressource (8 S., 89 KB)