On computing sparse generalized inverses

Abstract

The M-P (Moore-Penrose) pseudoinverse is used in several linear-algebra applications. It is convenient to construct sparse block-structured matrices satisfying some relevant properties of the M-P pseudoinverse for specific applications. Aiming at row-sparse generalized inverses, we consider 2,1-norm minimization (and generalizations). We show that a 2,1-norm minimizing generalized inverse satisfies two additional M-P properties, including one needed for computing least-squares solutions. We present formulations related to finding row-sparse generalized inverses that can be solved very efficiently, which we verify numerically.