A singular value p-shrinkage thresholding algorithm for low rank matrix recovery

摘要

In this paper, we propose an iterative singular value p-shrinkage thresholding algorithm for solving low rank matrix recovery problem, and also give its two accelerated versions using randomized singular value decomposition. The convergence result of the proposed singular value p-shrinkage thresholding algorithm is proved. Numerical results based on simulation data and real data show the effectiveness of all the three proposed algorithms compared to the existing state-of-the-art algorithms.