Publications related to Proximity Operators of Discrete Information Divergences

Non-convex optimization for robust multi-view imaging

We study the multi-view imaging problem where one has to reconstruct a set of l images, representing a single scene, from a few measurements made at different viewpoints. We first express the solution of the problem as the minimizer of a non-convex objecti ...

2013

Non-convex optimization for robust multi-view imaging

Pierre Vandergheynst, Gilles Puy

We study the multi-view imaging problem where one has to reconstruct a set of l images, representing a single scene, from a few measurements made at different viewpoints. We first express the solution of the problem as the minimizer of a non-convex objecti ...

2013

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

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

Volkan Cevher, Quoc Tran Dinh, Anastasios Kyrillidis

We propose an algorithmic framework for convex minimization problems of a composite function with two terms: a self-concordant function and a possibly nonsmooth regularization term. Our method is a new proximal Newton algorithm that features a local quadra ...

2013

Gabor dual windows using convex optimization

Nathanaël Perraudin

Redundant Gabor frames admit an infinite number of dual frames, yet only the canonical dual Gabor system, con- structed from the minimal l2-norm dual window, is widely used. This window function however, might lack desirable properties, such as good time-f ...

2013

Direct data-driven design of sparse controllers

Alireza Karimi

This paper deals with direct data-driven design of model-reference controllers whose number of parameters is constrained. Input-output (I/O) sparse controllers are introduced and proposed as an alternative to low-order controller tuning. The optimal I/O sp ...

IEEE2013

l0-deconvolution for compressive diffusion MRI

Jean-Philippe Thiran, Yves Wiaux, Alessandro Daducci, Anna Auria Rasclosa

Diffusion MRI is a well established imaging modality providing a powerful way to non-invasively probe the structure of the white matter. Despite the potential of the technique, the intrinsic long scan times of these sequences have hampered their use in cli ...

2013

Shaped Beam Synthesis of Arrays via Sequential Convex Optimizations

Juan Ramon Mosig, Anja Skrivervik, Benjamin Fuchs

A method to synthesize shaped beams with antenna arrays is presented. Specifically, the element excitations are determined such that the array radiates a power pattern that approximates a desired shape. To efficiently solve this problem, an iterative algor ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Database resources for the tuberculosis community

Stewart Cole, Jocelyne Lew, Ioannis Xenarios

Access to online repositories for genomic and associated "-omics" datasets is now an essential part of everyday research activity. It is important therefore that the Tuberculosis community is aware of the databases and tools available to them online, as we ...

Churchill Livingstone2013

Regularized Bundle Methods for Convex and Non-Convex Risks

Machine learning is most often cast as an optimization problem. Ideally, one expects a convex objective function to rely on efficient convex optimizers with nice guarantees such as no local optima. Yet, non-convexity is very frequent in practice and it may ...

2012

Proximity Operators of Discrete Information Divergences

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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

l0-deconvolution for compressive diffusion MRI

Shaped Beam Synthesis of Arrays via Sequential Convex Optimizations

Gabor dual windows using convex optimization

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

Non-convex optimization for robust multi-view imaging

Regularized Bundle Methods for Convex and Non-Convex Risks

Direct data-driven design of sparse controllers

Database resources for the tuberculosis community