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Singular Value Decomposition
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What is the general form of the Singular Value Decomposition (SVD) of a matrix?
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A
A = UΣV^T
💡 Explanation:
The SVD of a matrix A is given by A = UΣV^T, where U and V are orthogonal matrices and Σ is a diagonal matrix containing the singular values of A.