Matrix Completion via Sparse Factorization Solved by Accelerated Proximal Alternating Linearized Minimization

IEEE Transactions on Big Data, pp. 119-130, 2020.

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Abstract:

Classical matrix completion methods are not effective in recovering missing entries of data drawn from multiple subspaces because the matrices are often of high-rank. Recently a few advanced matrix completion methods were proposed to solve the problem but they are not scalable to large matrices and big data problems. This paper proposes a...More

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