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arxiv: 1812.04355 · v1 · pith:IG55VLJUnew · submitted 2018-12-11 · 🧮 math.OC · cs.IT· math.IT

Convex Regularization and Representer Theorems

classification 🧮 math.OC cs.ITmath.IT
keywords convexextremeapplicationsatomscombinationscommonconstantelements
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We establish a result which states that regularizing an inverse problem with the gauge of a convex set $C$ yields solutions which are linear combinations of a few extreme points or elements of the extreme rays of $C$. 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.

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