10 citations · 12 across the 4 of their papers we have counts for
4 papers
Screening Rules and its Complexity for Active Set Identification
Eugene Ndiaye, Olivier Fercoq, Joseph Salmon
Screening rules were recently introduced as a technique for explicitly identifying active structures such as sparsity, in optimization problem arising in machine learning. This has…
Refitting solutions promoted by sparse analysis regularization with block penalties
Charles-Alban Deledalle, Nicolas Papadakis, Joseph Salmon +1
In inverse problems, the use of an analysis regularizer induces a bias in the estimated solution. We propose a general refitting framework for removing this artifact wh…
Screening Rules for Lasso with Non-Convex Sparse Regularizers
Alain Rakotomamonjy, Gilles Gasso, Joseph Salmon
Leveraging on the convexity of the Lasso problem , screening rules help in accelerating solvers by discarding irrelevant variables, during the optimization process. However, becaus…
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…