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arxiv: 1806.09810 · v3 · pith:JPDRRF2Anew · submitted 2018-06-26 · 🧮 math.OC · cs.IT· math.IT

On Representer Theorems and Convex Regularization

classification 🧮 math.OC cs.ITmath.IT
keywords convexatomsextremeproblembroadercharacterizeclasscombinations
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We establish a general principle which states that regularizing an inverse problem with a convex function yields solutions which are convex combinations of a small number of atoms. These atoms are identified with the extreme points and elements of the extreme rays of the regularizer level sets. An extension to a broader class of quasi-convex regularizers is also discussed. As a side result, we characterize the minimizers of the total gradient variation, which was still an unresolved problem.

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    Proves eventual linear convergence for exchange and continuous methods in total variation minimization over measures under regularity conditions.