Earticle

The matrix completion problem is to reconstruct an unknown matrix with low-rank or approximately low-rank constraints from its partially known samples. Most methods to solve the rank minimization problem are relaxing it to the nuclear norm regularized least squares problem. Recently, there have been some simple and fast algorithms based on hard thresholding operator. In this paper, we propose an accelerated iterative hard thresholding method for matrix completion (AIHT). Then we report numerical results for solving noiseless and noisy matrix completion problems and image reconstruction. The numerical results suggest that significant improvement can be achieved by our algorithm compared to the other reported methods, especially in terms of CPU time.