A flexible framework for cubic regularization algorithms for non-convex optimization in function space

Title data

Schiela, Anton:
A flexible framework for cubic regularization algorithms for non-convex optimization in function space.
Hamburg-Harburg , 2014 . - 26 p. - (Bericht / Technische Universität Hamburg-Harburg, Institut für Mathematik ; 183 )

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Abstract in another language

We propose a cubic regularization algorithm that is constructed to deal with non-convex minimization problems in function space. It allows for a flexible choice of the regularization term and thus accounts for the fact that in such problems one often has to deal with more than one norm. Global and local convergence results are established in a general framework.