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Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm. (English) Zbl 1271.65083
The matrix completion problem is to recover a low-rank matrix from a subset of its entries. The authors propose a low-rank factorization model and construct a nonlinear succesive over-relaxation algorithm that only requires solving a linear least squares problem per iteration. Numerical experiments show that the algorithm can reliable solve a wide range of problems.

MSC:
65F30 Other matrix algorithms (MSC2010)
15A83 Matrix completion problems
15A23 Factorization of matrices
65F10 Iterative numerical methods for linear systems
65F20 Numerical solutions to overdetermined systems, pseudoinverses
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