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MiS Preprint
82/2011

Proximal Point Algorithm in Metric Spaces

Miroslav Bačák

Abstract

The proximal point algorithm, which is a well-known tool for finding minima of convex functions, is generalized from the classical Hilbert space framework into a nonlinear setting, namely, geodesic metric spaces of non-positive curvature. We prove that the sequence generated by the proximal point algorithm weakly converges to a minimizer, and also discuss a related question: convergence of the gradient flow.

Received:
Dec 9, 2011
Published:
Dec 9, 2011
Keywords:
proximal point algorithm, gradient flow semigroup, Nonpositive curvature

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