Fredrik Andersson

Non-Convex Rank/Sparsity Regularization and Local Minima

This paper considers the problem of recovering either a low rank matrix or a sparse vector from observations of linear combinations of the vector or matrix elements. Recent methods replace the non-convex regularization with l1 or nuclear norm relaxations. It is well known that this approach recovers…