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

URN to cite this document: urn:nbn:de:bvb:703-epub-3895-1

Title data

Schiela, Anton:
A flexible framework for cubic regularization algorithms for non-convex optimization in function space.
Bayreuth , 2017 . - 28 S.

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Abstract

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.

Further data

Item Type:	Preprint, postprint
Keywords:	non-convex optimization; optimization in function space; cubic regularization
Subject classification:	AMS MSC 2010: 49M37, 90C30
DDC Subjects:	500 Science > 510 Mathematics
Institutions of the University:	Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics) > Chair Mathematics V (Applied Mathematics) - Univ.-Prof. Dr. Lars Grüne Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Applied Mathematics Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Applied Mathematics > Chair Applied Mathematics - Univ.-Prof. Dr. Anton Schiela Profile Fields > Advanced Fields > Nonlinear Dynamics Faculties Faculties > Faculty of Mathematics, Physics und Computer Science Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics) Profile Fields Profile Fields > Advanced Fields
Language:	English
Originates at UBT:	Yes
URN:	urn:nbn:de:bvb:703-epub-3895-1
Date Deposited:	29 Oct 2018 13:17
Last Modified:	13 Mar 2019 14:04
URI:	https://epub.uni-bayreuth.de/id/eprint/3895

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