A Flexible Framework for Cubic Regularization Algorithms for Nonconvex Optimization in Function Space

We propose a cubic regularization algorithm that is constructed to deal with nonconvex 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 lo...

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Bibliographic Details

Published in:	Numerical functional analysis and optimization Vol. 40; no. 1; pp. 85 - 118
Main Author:	Schiela, Anton
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 02.01.2019 Taylor & Francis Ltd
Subjects:	Algorithms cubic regularization Function space Non-convex optimization Optimization optimization in function space Regularization Resorts & spas
ISSN:	0163-0563, 1532-2467
Online Access:	Get full text
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