Publications associées à Proximity Operators of Discrete Information Divergences

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To Convexify or Not? Regression with Clustering Penalties on Graphs

Volkan Cevher, Luca Baldassarre, Marwa El Halabi

We consider minimization problems that are compositions of convex functions of a vector

\x \in\reals^N

with submodular set functions of its support (i.e., indices of the non-zero coefficients of

\x

). Such problems are in general difficult for large

N

...

IEEE2013

Proximity Operators of Discrete Information Divergences

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Chattez avec Graph Search

Non-convex optimization for robust multi-view imaging

Non-convex optimization for robust multi-view imaging

To Convexify or Not? Regression with Clustering Penalties on Graphs

A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions

Gabor dual windows using convex optimization

Direct data-driven design of sparse controllers

l0-deconvolution for compressive diffusion MRI

Shaped Beam Synthesis of Arrays via Sequential Convex Optimizations

Database resources for the tuberculosis community

Regularized Bundle Methods for Convex and Non-Convex Risks

Shaped Beam Synthesis of Arrays via Sequential Convex Optimizations

Non-convex optimization for robust multi-view imaging

Non-convex optimization for robust multi-view imaging

Direct data-driven design of sparse controllers

l0-deconvolution for compressive diffusion MRI

A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions

Database resources for the tuberculosis community

Regularized Bundle Methods for Convex and Non-Convex Risks

Gabor dual windows using convex optimization

To Convexify or Not? Regression with Clustering Penalties on Graphs