Singular Value Decomposition

Singular Value Decomposition (SVD) is one of matrix factorization techniques. It has a broad range of applications including dimensionality reduction, solving linear inverse problems, and data fitting.

Note

For more information on the concepts behind the algorithm, see "Details" section.

For more information on the algorithm's parameters for a specific computation mode and examples of its usage, see "Batch Processing", "Online Processing" and "Distributed Processing" sections.

For more complete information about compiler optimizations, see our Optimization Notice.
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