Linear Convergence

Low-rank matrix recovery problems are ubiquitous in many areas of science and engineering. One approach to solve these problems is Nuclear Norm Minimization, which is itself computationally challenging to solve. Iteratively Reweighted Least Squares …

The recovery of sparse data is at the core of many applications in machine learning and signal processing. While such problems can be tackled using $\ell_1$-regularization as in the LASSO estimator and in the Basis Pursuit approach, specialized …