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Optimization
A Journal of Mathematical Programming and Operations Research
Volume 51, 2002 - Issue 2
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Original Articles

Proximal Point Algorithm On Riemannian Manifolds

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Pages 257-270 | Received 10 Aug 1999, Published online: 10 Jan 2008
 

Abstract

In this paper we consider the minimization problem with constraints. We will show that if the set of constraints is a Riemannian manifold of nonpositive sectional curvature, and the objective function is convex in this manifold, then the proximal point method in Euclidean space is naturally extended to solve that class of problems. We will prove that the sequence generated by our method is well defined and converge to a minimizer point. In particular we show how tools of Riemannian geometry, more specifically the convex analysis in Riemannian manifolds, can be used to solve nonconvex constrained problem in Euclidean, space.

Additional information

Notes on contributors

P. R. Oliveira

Research of this author was partially supported by CNPq, Brazil

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