Matrix completion using nuclear norm, spectral norm or weighted nuclear norm minimization.
Completes a matrix with missing entries, such that the obtained matrix has minimal norm.
Usage:
[CompletedMat, ier] = MatrixCompletion(A.*B, B,N, mode, lambda_tol, tol, display);
A - matrix to complete
B - binary matrix indicates values or missing entries in A (same size, 1 - known value, 0 - missing value)
N - number of iterations
mode - working mode: can be 'nuclear', 'spectral'
lambda_tol - tolerance value from the nuclear/spectral norm minimal value
tol - tolerance on the known entries
Output:
CompletedMat - completed matrix
ier - error indicator: 0 - OK, 1 - Failed to converge (probably needs more iterations).
For a demonstration, run demo.m
The code is based on the paper:
G. Shabat, A. Averbuch "Interest Zone Matrix Approximation", Electronic journal of Linear Algebra, Vol. 23(1), 2012.
Note: The package contains other useful code such as approximating a matrix under different constraints by taking all of it into account or just part of its entries.
Cite As
Gil Shabat (2024). Matrix completion using nuclear norm, spectral norm or weighted nuclear norm minimization. (https://www.mathworks.com/matlabcentral/fileexchange/50056-matrix-completion-using-nuclear-norm-spectral-norm-or-weighted-nuclear-norm-minimization), MATLAB Central File Exchange. Retrieved .
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- Sciences > Physics >
- Sciences > Physics > Particle & Nuclear Physics >
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Version | Published | Release Notes | |
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2.0.0.0 | 1) demo.m fixed according to comments
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1.1.0.0 | Description slightly modified. |
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1.0.0.0 |