Publications associées à Sparse Approximation by Linear Programming: Measuring the Error with the $ell_1$ Norm

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Coding Structure and Replication Optimization for Interactive Multiview Video Streaming

Pascal Frossard

Multiview video refers to videos of the same dynamic 3-D scene captured simultaneously by multiple closely spaced cameras from different viewpoints. We study interactive streaming of pre-encoded multiview videos, where, at any time, a client can request an ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Jump-Sparse and Sparse Recovery Using Potts Functionals

Martin Kurt Storath

We recover jump-sparse and sparse signals from blurred incomplete data corrupted by (possibly non-Gaussian) noise using inverse Potts energy functionals. We obtain analytical results (existence of minimizers, complexity) on inverse Potts functionals and pr ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Sparsity in tensor optimization for optical-interferometric imaging

Jean-Philippe Thiran, Yves Wiaux, Rafael Eduardo Carrillo Rangel, Anna Auria Rasclosa

Image recovery in optical interferometry is an ill-posed nonlinear inverse problem arising from incomplete power spectrum and bispectrum measurements. We review our previous work, which reformulates this nonlinear problem in the framework of tensor recover ...

IEEE2014

Sparse projections onto the simplex

Volkan Cevher, Christoph Koch, Anastasios Kyrillidis

Most learning methods with rank or sparsity constraints use convex relaxations, which lead to optimization with the nuclear norm or the`1-norm. However, several important learning applications cannot benet from this approach as they feature these convex no ...

JMLR W&CP2013

Anisotropic Interpolation of Sparse Generalized Image Samples

Michaël Unser, Aurélien Bourquard

Practical image-acquisition systems are often modeled as a continuous-domain prefilter followed by an ideal sampler, where generalized samples are obtained after convolution with the impulse response of the device. In this paper, our goal is to interpolate ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Bearing estimation via spatial sparsity using compressive sensing

Volkan Cevher

Bearing estimation algorithms obtain only a small number of direction of arrivals (DOAs) within the entire angle domain, when the sources are spatially sparse. Hence, we propose a method to specifically exploit this spatial sparsity property. The method us ...

Institute of Electrical and Electronics Engineers2012

Hard Thresholding with Norm Constraints

Volkan Cevher, Gilles Puy, Anastasios Kyrillidis

We introduce a new sparse recovery paradigm, called Normed Pursuits, where efficient algorithms from combinatorial and convex optimization interface for interpretable and model-based solutions. Synthetic and real data experiments illustrate that Normed Pur ...

Ieee2012

Efficient Image Reconstruction Under Sparsity Constraints With Application To Mri And Bioluminescence Tomography

Michaël Unser, Matthieu Guerquin-Kern, Jean-Charles Baritaux

Most bioimaging modalities rely on indirect measurements of the quantity under investigation. The image is obtained as the result of an optimization problem involving a physical model of the measurement system. Due to the ill-posedness of the above problem ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Sparse Approximation by Linear Programming: Measuring the Error with the $ell_1$ Norm

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A totally unimodular view of structured sparsity

Coding Structure and Replication Optimization for Interactive Multiview Video Streaming

Jump-Sparse and Sparse Recovery Using Potts Functionals

Sparsity in tensor optimization for optical-interferometric imaging

Sparse projections onto the simplex

Anisotropic Interpolation of Sparse Generalized Image Samples

Bearing estimation via spatial sparsity using compressive sensing

Hard Thresholding with Norm Constraints

Efficient Image Reconstruction Under Sparsity Constraints With Application To Mri And Bioluminescence Tomography

Sparsity & [and] dictionaries - algorithms & [and] design

Bearing estimation via spatial sparsity using compressive sensing

Jump-Sparse and Sparse Recovery Using Potts Functionals

Anisotropic Interpolation of Sparse Generalized Image Samples

Sparsity in tensor optimization for optical-interferometric imaging

Sparse projections onto the simplex

Efficient Image Reconstruction Under Sparsity Constraints With Application To Mri And Bioluminescence Tomography

Coding Structure and Replication Optimization for Interactive Multiview Video Streaming

Hard Thresholding with Norm Constraints

Sparsity & [and] dictionaries - algorithms & [and] design

A totally unimodular view of structured sparsity