Iteratively re-weighted least squares minimization for sparse recovery
Daubechies, Ingrid ; DeVore, Ronald ; Fornasier, Massimo ; Gunturk, C. Sinan
arXiv, 0807.0575 / Harvested from arXiv
Text on arXiv
We analyze an Iteratively Re-weighted Least Squares (IRLS) algorithm for promoting l1-minimization in sparse and compressible vector recovery. We prove its convergence and we estimate its local rate. We show how the algorithm can be modified in order to promote lt-minimization for t<1, and how this modification produces superlinear rates of convergence.
Publié le : 2008-07-03
Classification:  Mathematics - Numerical Analysis,  65K10 
@article{0807.0575,
     author = {Daubechies, Ingrid and DeVore, Ronald and Fornasier, Massimo and Gunturk, C. Sinan},
     title = {Iteratively re-weighted least squares minimization for sparse recovery},
     journal = {arXiv},
     volume = {2008},
     number = {0},
     year = {2008},
     language = {en},
     url = {http://dml.mathdoc.fr/item/0807.0575}
}

Daubechies, Ingrid; DeVore, Ronald; Fornasier, Massimo; Gunturk, C. Sinan. Iteratively re-weighted least squares minimization for sparse recovery. arXiv, Tome 2008 (2008) no. 0, . http://gdmltest.u-ga.fr/item/0807.0575/