A Continuous Exact $\ell_0$ Penalty (CEL0) for Least Squares Regularized Problem, SIAM Journal on Imaging Sciences, vol.8, issue.3, 2015. ,
DOI : 10.1137/151003714
For most large underdetermined systems of linear equations the minimal ???1-norm solution is also the sparsest solution, Communications on Pure and Applied Mathematics, vol.50, issue.6, pp.797-829, 2006. ,
DOI : 10.1002/cpa.20132
Greedy approximation, Acta Numerica, vol.17, pp.235-409, 2008. ,
DOI : 10.1017/cbo9780511762291
Feature selection in machine learning: an exact penalty approach using a Difference of Convex function Algorithm, Machine Learning, pp.1-24, 2014. ,
DOI : 10.1007/s10994-014-5455-y
Iterative Thresholding for Sparse Approximations, Journal of Fourier Analysis and Applications, vol.73, issue.10, pp.629-654, 2008. ,
DOI : 10.1007/s00041-008-9035-z
Description of the Minimizers of Least Squares Regularized with $\ell_0$-norm. Uniqueness of the Global Minimizer, SIAM Journal on Imaging Sciences, vol.6, issue.2, pp.904-937, 2013. ,
DOI : 10.1137/11085476X
On Iteratively Reweighted Algorithms for Nonsmooth Nonconvex Optimization in Computer Vision, SIAM Journal on Imaging Sciences, vol.8, issue.1, pp.331-372, 2015. ,
DOI : 10.1137/140971518
Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward???backward splitting, and regularized Gauss???Seidel methods, Mathematical Programming, pp.91-129, 2013. ,
DOI : 10.1007/s10107-011-0484-9
URL : https://hal.archives-ouvertes.fr/inria-00636457