MATRIX ALPS: Accelerated low rank and sparse matrix reconstruction
MATRIX ALPS: Accelerated low rank and sparse matrix reconstruction
We propose MATRIX ALPS for recovering a sparse plus low-rank decomposition of a matrix given its corrupted and incomplete linear measurements. Our approach is a first-order projected gradient method over non-convex sets, and it exploits a well-known memory-based acceleration technique. We theoretically characterize the convergence properties of MATRIX ALPS using …