A Flexible Framework for Cubic Regularization Algorithms for Nonconvex Optimization in Function Space. (2nd January 2019)

• Record Type: Journal Article
• Authors: Schiela, Anton
• Is Part Of: Numerical functional analysis and optimization. Volume 40:Number 1(2019)
• Page Start: 85
• Page End: 118
• Publication Date: 2019-01-02
• Subjects: Non-convex optimization -- optimization in function space -- cubic regularization; 49M37 -- 90C30; Functional analysis -- Periodicals; Numerical analysis -- Periodicals; Mathematical optimization -- Periodicals; Numerical Analysis, Computer-Assisted; 515.705
• DOI: 10.1080/01630563.2018.1499114
• Languages: English
• ISSNs: 0163-0563

Abstract

Abstract: 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 local convergence results are established in a general framework.