Functions with Bounded Hessian–Schatten Variation: Density, Variational, and Extremality Properties

Author:

Ambrosio Luigi,Brena Camillo,Conti Sergio

Abstract

AbstractIn this paper we analyze in detail a few questions related to the theory of functions with bounded p-Hessian–Schatten total variation, which are relevant in connection with the theory of inverse problems and machine learning. We prove an optimal density result, relative to the p-Hessian–Schatten total variation, of continuous piecewise linear (CPWL) functions in any space dimension d, using a construction based on a mesh whose local orientation is adapted to the function to be approximated. We show that not all extremal functions with respect to the p-Hessian–Schatten total variation are CPWL. Finally, we prove the existence of minimizers of certain relevant functionals involving the p-Hessian–Schatten total variation in the critical dimension $$d=2$$ d = 2 .

Funder

Ministero dell’ Istruzione, dell Università e della Ricerca

Scuola Normale Superiore

Publisher

Springer Science and Business Media LLC

Subject

Mechanical Engineering,Mathematics (miscellaneous),Analysis

Reference20 articles.

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1. Linear inverse problems with Hessian–Schatten total variation;Calculus of Variations and Partial Differential Equations;2023-11-20

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