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Steepest†descent proximal point algorithms for a class of variational inequalities in Banach spaces

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  • Nguyen Buong

Abstract

In this paper, we present a new approach to the problem of finding a common zero for a system of m†accretive mappings in a uniformly convex Banach space with a uniformly Gâteaux differentiable norm. We propose an implicit iteration method and two explicit ones, based on compositions of resolvents with the steepest†descent method. We show that our results contain some iterative methods in literature as special cases. An extension of the Xu's regularization method for the proximal point algorithm from Hilbert spaces onto Banach ones under simple conditions of convergence and a new variant for the method of alternating resolvents are obtained. Numerical experiments are given to affirm efficiency of the methods.

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  • Nguyen Buong, 2018. "Steepest†descent proximal point algorithms for a class of variational inequalities in Banach spaces," Mathematische Nachrichten, Wiley Blackwell, vol. 291(8-9), pages 1191-1207, June.
    • Handle: RePEc:bla:mathna:v:291:y:2018:i:8-9:p:1191-1207
    DOI: 10.1002/mana.201600240
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