Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm (Q1946921)
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scientific article; zbMATH DE number 6152666
| Language | Label | Description | Also known as |
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| English | Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm |
scientific article; zbMATH DE number 6152666 |
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Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm (English)
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10 April 2013
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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.
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matrix completion
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alternating minimization
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nonlinear GS method
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nonlinear SOR method
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low-rank factorization model
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nonlinear succesive over-relaxation algorithm
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linear least squares problem
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numerical experiments
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