A fast randomized algorithm for overdetermined linear least-squares regression

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چکیده

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A fast randomized algorithm for overdetermined linear least-squares regression.

We introduce a randomized algorithm for overdetermined linear least-squares regression. Given an arbitrary full-rank m x n matrix A with m >/= n, any m x 1 vector b, and any positive real number epsilon, the procedure computes an n x 1 vector x such that x minimizes the Euclidean norm ||Ax - b || to relative precision epsilon. The algorithm typically requires ((log(n)+log(1/epsilon))mn+n(3)) fl...

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ژورنال

عنوان ژورنال: Proceedings of the National Academy of Sciences

سال: 2008

ISSN: 0027-8424,1091-6490

DOI: 10.1073/pnas.0804869105