A Singular Value Thresholding with Diagonal-Update Algorithm for Low-Rank Matrix Completion

Abstract EN

The singular value thresholding (SVT) algorithm plays an important role in the well-known matrix reconstruction problem, and it has many applications in computer vision and recommendation systems.

In this paper, an SVT with diagonal-update (D-SVT) algorithm was put forward, which allows the algorithm to make use of simple arithmetic operation and keep the computational cost of each iteration low.

The low-rank matrix would be reconstructed well.

The convergence of the new algorithm was discussed in detail.

Finally, the numerical experiments show the effectiveness of the new algorithm for low-rank matrix completion.