Publications associées à Sparsity-Inducing Reconstruction Methods for Fluorescence Diffuse Optical Tomography

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Sparsistency of $\ell_1$-Regularized $M$-Estimators

Volkan Cevher, Jonathan Mark Scarlett, Yen-Huan Li

We consider the model selection consistency or sparsistency of a broad set of

\ell_1

-regularized

M

-estimators for linear and non-linear statistical models in a unified fashion. For this purpose, we propose the local structured smoothness condition (LSS ...

2015

Sparsity-Inducing Reconstruction Methods for Fluorescence Diffuse Optical Tomography

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Sparsistency of $\ell_1$-Regularized $M$-Estimators

Jump-Sparse and Sparse Recovery Using Potts Functionals

Sparse regularization for fiber ODF reconstruction: from the suboptimality of $\ell_2$ and $\ell_1$ priors to $\ell_0$

Robust image reconstruction from multi-view measurements

On Sparsity Averaging

Poisson Image Reconstruction With Hessian Schatten-Norm Regularization

Sparsity averaging for radio-interferometric imaging

Application of a New Sensing Principle for Photoacoustic Imaging of Point Absorbers

Sparse Distributed Learning Based on Diffusion Adaptation

Binary Compressed Imaging

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Jump-Sparse and Sparse Recovery Using Potts Functionals

Sparse regularization for fiber ODF reconstruction: from the suboptimality of $\ell_2$ and $\ell_1$ priors to $\ell_0$

Binary Compressed Imaging

Robust image reconstruction from multi-view measurements

On Sparsity Averaging

Poisson Image Reconstruction With Hessian Schatten-Norm Regularization

Sparsity averaging for radio-interferometric imaging

Application of a New Sensing Principle for Photoacoustic Imaging of Point Absorbers

Sparse Distributed Learning Based on Diffusion Adaptation