The Singular Value Decomposition Saves the Universe - MATLAB
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    The Singular Value Decomposition Saves the Universe

    The Singular Value Decomposition, or SVD, is the Swiss Army knife of technical computation. Its wide variety of applications includes principal component analysis, the foundation of modern data analytics. A pioneering computer graphics film made in 1976 at Los Alamos displays what was then a newly discovered algorithm for computing the SVD. Hollywood borrowed the graphics. However, MATLAB® and the SVD were not enough to save one of the biggest failures in the history of Silicon Valley.

    Recorded: 3 Nov 2016

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    The SVD factors each matrix <em>A</em> into an orthogonal matrix <em>U</em> times a diagonal matrix Σ (the singular value) times another orthogonal matrix V<sup>T</sup>: rotation times stretch times rotation.

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