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The proximal point algorithm in metric spaces (1206.7074v1)

Published 29 Jun 2012 in math.OC and math.MG

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 nonpositive 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.

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