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Randomized algorithms for matrices and data

Randomized algorithms for matrices and data. Michael W. Mahoney Stanford University November 2011 (For more info, see: http://cs.stanford.edu/people/mmahoney). Matrix computations. Eigendecompositions, QR, SVD, least-squares, etc. Traditional algorithms:

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Randomized algorithms for matrices and data