Linear Inverse Problems with Hessian-Schatten Total Variation

2022/10/08 by Luigi Ambrosio, Shayan Aziznejad, Ambrosio, Luigi +5 · 4 citations
Mathematics · #Analytic and geometric function theory #FOS: Mathematics #Functional Analysis (math.FA) #Numerical methods in inverse problems #Point processes and geometric inequalities

paper · pdf · doi:10.48550/arxiv.2210.04077

openalex publication_date 2022/10/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper, we characterize the class of extremal points of the unit ball of the Hessian-Schatten total variation (HTV) functional. The underlying motivation for our work stems from a general representer theorem that characterizes the solution set of regularized linear inverse problems in terms of the extremal points of the regularization ball. Our analysis is mainly based on studying the class of continuous and piecewise linear (CPWL) functions. In particular, we show that in dimension d=2, CPWL functions are dense in the unit ball of the HTV functional. Moreover, we prove that a CPWL function is extremal if and only if its Hessian is minimally supported. For the converse, we prove that the density result (which we have only proven for dimension d = 2) implies that the closure of the CPWL extreme points contains all extremal points.

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• Variational Tensor-Product Splines
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• Decoupled Solution for Composite Sparse-plus-Smooth Inverse Problems
• Mixed-Derivative Total Variation

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