Gauss–Newton method for convex composite optimizations on Riemannian manifolds

Gauss–Newton method for convex composite optimizations on Riemannian manifolds

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Article ID: iaor20123826
Volume: 53
Issue: 1
Start Page Number: 5
End Page Number: 28
Publication Date: May 2012
Journal: Journal of Global Optimization
Authors: , ,
Keywords: Newton method
Abstract:

A notion of quasi‐regularity is extended for the inclusion problem F ( p ) C equ1 , where F is a differentiable mapping from a Riemannian manifold M to n equ2 . When C is the set of minimum points of a convex real‐valued function h on n equ3 and DF satisfies the L‐average Lipschitz condition, we use the majorizing function technique to establish the semi‐local convergence of sequences generated by the Gauss‐Newton method (with quasi‐regular initial points) for the convex composite function hF on Riemannian manifold. Two applications are provided: one is for the case of regularities on Riemannian manifolds and the other is for the case when C is a cone and DF(p 0)(·) - C is surjective. In particular, the results obtained in this paper extend the corresponding one in Wang et al. (2009).

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