On the Convergence Rate of an Inexact Proximal Point Algorithm for Quasiconvex Minimization on Hadamard Manifolds

Nancy Baygorrea, Erik Alex Papa Quiroz, Nelson Maculan

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

4 Citas (Scopus)

Resumen

In this paper, we present an analysis about the rate of convergence of an inexact proximal point algorithm to solve minimization problems for quasiconvex objective functions on Hadamard manifolds. We prove that under natural assumptions the sequence generated by the algorithm converges linearly or superlinearly to a critical point of the problem.

Idioma originalInglés
Páginas (desde-hasta)457-467
Número de páginas11
PublicaciónJournal of the Operations Research Society of China
Volumen5
N.º4
DOI
EstadoPublicada - 1 dic 2017

Nota bibliográfica

Publisher Copyright:
© 2016, Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press, and Springer-Verlag Berlin Heidelberg.

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