59 citations · 443 across the 46 of their papers we have counts for
7 papers · 1 filter
Characterizing the maximum parameter of the total-variation denoising through the pseudo-inverse of the divergence
Charles-Alban Deledalle, Nicolas Papadakis, Joseph Salmon +1
We focus on the maximum regularization parameter for anisotropic total-variation denoising. It corresponds to the minimum value of the regularization parameter above which the solu…
Gap Safe screening rules for sparsity enforcing penalties
Eugene Ndiaye, Olivier Fercoq, Alexandre Gramfort +1
In high dimensional regression settings, sparsity enforcing penalties have proved useful to regularize the data-fitting term. A recently introduced technique called screening rules…
Efficient Smoothed Concomitant Lasso Estimation for High Dimensional Regression
Eugene Ndiaye, Olivier Fercoq, Alexandre Gramfort +2
In high dimensional settings, sparse structures are crucial for efficiency, both in term of memory, computation and performance. It is customary to consider penalty to enf…
Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions
Igor Colin, Aurélien Bellet, Joseph Salmon +1
In decentralized networks (of sensors, connected objects, etc.), there is an important need for efficient algorithms to optimize a global cost function, for instance to learn a glo…
CLEAR: Covariant LEAst-square Re-fitting with applications to image restoration
C-A. Deledalle, N. Papadakis, J. Salmon +1
In this paper, we propose a new framework to remove parts of the systematic errors affecting popular restoration algorithms, with a special focus for image processing tasks. Genera…
Adapting to unknown noise level in sparse deconvolution
Claire Boyer, Yohann De Castro, Joseph Salmon
In this paper, we study sparse spike deconvolution over the space of complex-valued measures when the input measure is a finite sum of Dirac masses. We introduce a modified version…