Calculus of Variations and Geometric Measure Theory

M. Carioni - J. A. Iglesias - D. Walter

Extremal points and sparse optimization for generalized Kantorovich-Rubinstein norms

created by carioni on 23 Feb 2024
modified by iglesias on 10 Apr 2024

[BibTeX]

Published Paper

Inserted: 23 feb 2024
Last Updated: 10 apr 2024

Journal: Foundations of Computational Mathematics
Year: 2024

ArXiv: 2209.09167 PDF

Abstract:

A precise characterization of the extremal points of sublevel sets of nonsmooth penalties provides both detailed information about minimizers, and optimality conditions in general classes of minimization problems involving them. Moreover, it enables the application of accelerated generalized conditional gradient methods for their efficient solution. In this manuscript, this program is adapted to the minimization of a smooth convex fidelity term which is augmented with an unbalanced transport regularization term given in the form of a generalized Kantorovich-Rubinstein norm for Radon measures. More precisely, we show that the extremal points associated to the latter are given by all Dirac delta functionals supported in the spatial domain as well as certain dipoles, i.e., pairs of Diracs with the same mass but with different signs. Subsequently, this characterization is used to derive precise first-order optimality conditions as well as an efficient solution algorithm for which linear convergence is proved under natural assumptions. This behaviour is also reflected in numerical examples for a model problem.


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