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On the Convergence Rate of an Inexact Proximal Point Algorithm for Quasiconvex Minimization on Hadamard Manifolds
Online published: 2017-12-30
Supported by
This work was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior of the Federal University of Rio de Janeiro (UFRJ), Brazil.
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.
Nancy Baygorrea, Erik Alex Papa Quiroz, Nelson Maculan . On the Convergence Rate of an Inexact Proximal Point Algorithm for Quasiconvex Minimization on Hadamard Manifolds[J]. Journal of the Operations Research Society of China, 2017 , 5(4) : 457 -467 . DOI: 10.1007/s40305-016-0129-z
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