We prove new results about the robustness of noise-blind decoders for the problem of re- constructing a sparse vector from underdetermined linear measurements. Our results imply provable robustness of equality-constrained l1-minimization for random …
We propose a new iteratively reweighted least squares (IRLS) algorithm for the recovery of a matrix of rank from incomplete linear observations, solv- ing a sequence of low complexity linear …
This is a first conference version of the paper on Harmonic Mean Iteratively Reweighted Least Squares.