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- W2801678411 abstract "In this paper, we propose a new subspace-approximating algorithm for matrix completion based on the subspace-approximating of the singular value decomposition.Then we use quadratic programming to produce the closest and the best feasible matrix in the subspace. This algorithm can achieve the reduction of the rank of the subspace by gradually reducing the number of the singular value of the thresholding and get the optimal low-rank matrix. It is proved that the subspace-approximating algorithm is convergent under some conditions. Besides, compared with the augmented Lagrange multiplier algorithm and orthogonal rank-one matrix pursuit algorithm by random experiments,the proposed algorithm is more effective in the CPU time and the low-rank property." @default.
- W2801678411 created "2018-05-17" @default.
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- W2801678411 date "2018-04-08" @default.
- W2801678411 modified "2023-09-26" @default.
- W2801678411 title "A subspace-approximating algorithm for matrix completion" @default.
- W2801678411 doi "https://doi.org/10.1360/n012016-00025" @default.
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