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This manuscript describes a technique for computing partial rank-revealing factorizations, such as, e.g, a partial QR factorization or a partial singular value decomposition.
Carl Eckart and Gale Young, The approximation of one matrix by another of lower rank , Psychometrika 1
1936
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Youcef Saad, Overview of Krylov subspace methods with applications to control problems , Signal processing, scattering and operator theory, and numerical methods (Amsterdam, 1989), Progr. Systems Control Theory, vol. 5, Birkhäuser Boston, Boston, MA, 1990, pp. 401–410. MR 1115470
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Ming Gu and Stanley C. Eisenstat, Efficient algorithms for computing a strong rank-revealing QR factorization , SIAM J. Sci. Comput. 17
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H. Cheng, Z. Gimbutas, P.G. Martinsson, and V. Rokhlin, On the compression of low rank matrices , SIAM Journal of Scientific Computing 26
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Per-Gunnar Martinsson, Vladimir Rokhlin, and Mark Tygert, A randomized algorithm for the approximation of matrices , Tech. Report Yale CS research report YALEU/DCS/RR-1361, Yale University, Computer Science Department, 2006
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Vladimir Rokhlin, Arthur Szlam, and Mark Tygert, A randomized algorithm for principal component analysis , SIAM Journal on Matrix Analysis and Applications 31
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Nathan Halko, Per-Gunnar Martinsson, and Joel A. Tropp, Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions , SIAM Review 53
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by same author, A randomized algorithm for the decomposition of matrices , Appl. Comput. Harmon. Anal. 30
2011
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Gene H. Golub and Charles F. Van Loan, Matrix computations , fourth ed., Johns Hopkins Studies in the Mathematical Sciences, Johns Hopkins University Press, Baltimore, MD, 2013. MR 3024913
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Later among the works it cites.
2014
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S. Voronin and P.-G. Martinsson, A CUR Factorization Algorithm based on the Interpolative Decomposition , ArXiv e-prints (2014)
2014
Later among the works it cites.
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