English

Convex Regularization and Representer Theorems

Optimization and Control 2018-12-12 v1 Information Theory math.IT

Abstract

We establish a result which states that regularizing an inverse problem with the gauge of a convex set CC yields solutions which are linear combinations of a few extreme points or elements of the extreme rays of CC. These can be understood as the \textit{atoms} of the regularizer. We then explicit that general principle by using a few popular applications. In particular, we relate it to the common wisdom that total gradient variation minimization favors the reconstruction of piecewise constant images.

Keywords

Cite

@article{arxiv.1812.04355,
  title  = {Convex Regularization and Representer Theorems},
  author = {Claire Boyer and Antonin Chambolle and Yohann de Castro and Vincent Duval and Frédéric de Gournay and Pierre Weiss},
  journal= {arXiv preprint arXiv:1812.04355},
  year   = {2018}
}

Comments

in Proceedings of iTWIST'18, Paper-ID: 30, Marseille, France, November, 21-23, 2018

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