We consider a variable metric linesearch based proximal gradient method for the minimization of the sum of a smooth, possibly nonconvex function plus a convex, possibly nonsmooth term. We prove convergence of this iterative algorithm to a critical point if the objective function satisfies the Kurdyka- Lojasiewicz property at each point of its domain, under the assumption that a limit point exists. The proposed method is applied to a wide collection of image processing problems and our numerical tests show that our algorithm results to be flexible, robust and competitive when compared to recently proposed approaches able to address the optimization problems arising in the considered applications.

On the convergence of a linesearch based proximal-gradient method for nonconvex optimization / Bonettini, Silvia; Loris, Ignace; Porta, Federica; Prato, Marco; Rebegoldi, Simone. - In: INVERSE PROBLEMS. - ISSN 0266-5611. - STAMPA. - 33:5(2017), pp. 1-27. [10.1088/1361-6420/aa5bfd]

On the convergence of a linesearch based proximal-gradient method for nonconvex optimization

BONETTINI, Silvia;Porta, Federica;PRATO, Marco;REBEGOLDI, SIMONE
2017

Abstract

We consider a variable metric linesearch based proximal gradient method for the minimization of the sum of a smooth, possibly nonconvex function plus a convex, possibly nonsmooth term. We prove convergence of this iterative algorithm to a critical point if the objective function satisfies the Kurdyka- Lojasiewicz property at each point of its domain, under the assumption that a limit point exists. The proposed method is applied to a wide collection of image processing problems and our numerical tests show that our algorithm results to be flexible, robust and competitive when compared to recently proposed approaches able to address the optimization problems arising in the considered applications.
3-mar-2017
33
5
1
27
On the convergence of a linesearch based proximal-gradient method for nonconvex optimization / Bonettini, Silvia; Loris, Ignace; Porta, Federica; Prato, Marco; Rebegoldi, Simone. - In: INVERSE PROBLEMS. - ISSN 0266-5611. - STAMPA. - 33:5(2017), pp. 1-27. [10.1088/1361-6420/aa5bfd]
Bonettini, Silvia; Loris, Ignace; Porta, Federica; Prato, Marco; Rebegoldi, Simone
File in questo prodotto:
File Dimensione Formato  
VOR_On the convergence of a linesearch.pdf

non disponibili

Tipologia: Versione dell'editore (versione pubblicata)
Dimensione 3.55 MB
Formato Adobe PDF
3.55 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/1123402
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 29
  • ???jsp.display-item.citation.isi??? 20
social impact