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• W4285187650 abstract "In recent years, the problem of recovering a low-rank matrix from partial entries, known as low-rank matrix completion problem, has attracted much attention in many applications. However, it is a NP-hard problem due to the nonconvexity nature of the matrix rank function. In this paper, a rank Laplace function is studied to recover the low-rank matrices. Firstly, we propose an iterative Laplace thresholding algorithm to solve the regularized Laplace low-rank matrix completion problem. Secondly, some other iterative thresholding algorithms are designed to recover the low-rank matrices. Finally, we provide a series of numerical simulations to test the proposed algorithms on some low-rank matrix completion and image inpainting problems, and the results show that our algorithms perform better than some state-of-art methods in recovering the low-rank matrices." @default.
• W4285187650 created "2022-07-14" @default.
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• W4285187650 date "2022-01-01" @default.
• W4285187650 modified "2023-10-04" @default.
• W4285187650 title "A Nonconvex Method to Low-Rank Matrix Completion" @default.
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• W4285187650 doi "https://doi.org/10.1109/access.2022.3177592" @default.
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