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Found 4 papers, 2 papers with code
Difference of Submodular Minimization via DC Programming
We introduce variants of DCA and its complete form (CDCA) that we apply to the DC program corresponding to DS minimization.
The Maximum Entropy on the Mean Method for Image Deblurring
Image deblurring is a notoriously challenging ill-posed inverse problem.
A principled approach for generating adversarial images under non-smooth dissimilarity metrics
This includes, but is not limited to, $\ell_1, \ell_2$, and $\ell_\infty$ perturbations; the $\ell_0$ counting "norm" (i. e. true sparseness); and the total variation seminorm, which is a (non-$\ell_p$) convolutional dissimilarity measuring local pixel changes.
Convex Geometry of the Generalized Matrix-Fractional Function
Generalized matrix-fractional (GMF) functions are a class of matrix support functions introduced by Burke and Hoheisel as a tool for unifying a range of seemingly divergent matrix optimization problems associated with inverse problems, regularization and learning.
