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A classical problem in matrix computations is the efficient and reliable approximation of a given matrix by a matrix of lower rank.
The approximation of one matrix by another of lower rank
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On the existence and computation of rank-revealing LU factorizations
C.-T. Pan · 1996
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A fast randomized algorithm for the approximation of matrices
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Text datasets in matlab format
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A fast and efficient algorithm for low-rank approximation of a matrix
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A randomized algorithm for principal component analysis
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Symmetry, probability, and recognition in face space
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Superfast multifrontal method for large structured linear systems of equations
J. Xia, S. Chandrasekaran, M. Gu, and X. S. Li · 2009
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A fast randomized algorithm for computing a hierarchically semi-separable representation of a matrix
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J. Xia and M. Gu · 2010
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New efficient and robust HSS cholesky factorization of spd matrices
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Regularization with randomized SVD for large-scale discrete inverse problems
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