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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >A Singular Value Thresholding with Diagonal-Update Algorithm for Low-Rank Matrix Completion
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A Singular Value Thresholding with Diagonal-Update Algorithm for Low-Rank Matrix Completion

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

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摘要

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.

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