Department of Mathematics and Department of Electrical and Computer Engineering, Technical University of Munich; Department of Mathematics, KU Eichstätt–Ingolstadt; Department of Applied Mathematics & Statistics, Johns Hopkins University
Christian Kümmerle, Claudio Mayrink Verdun, Dominik Stöger
compressed sensing;sparse models;signal processing;iteratively reweighted least squares;convex optimization;linear convergence
Iteratively Reweighted Least Squares for Basis Pursuit with Global Linear Convergence Rate