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The CUR matrix decomposition and the Nystr\"{o}m approximation are two important low-rank matrix approximation techniques.
Rank and null space calculations using matrix decomposition without column interchanges
L. V. Foster · 1986
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Rank revealing QR factorizations
T. F. Chan · 1987
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Low-dimensional procedure for the characterization of human faces
L. Sirovich and M. Kirby · 1987
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Indexing by latent semantic analysis
S. Deerwester, S. T. Dumais, G. W. Furnas, T. K. Landauer, and R. Harshman · 1990
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Structure-preserving and rank-revealing QR-factorizations
C. H. Bischof and P. C. Hansen · 1991
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Eigenfaces for recognition
M. Turk and A. Pentland · 1991
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Rank-revealing QR factorizations and the singular value decomposition
Y. P. Hong and C. T. Pan · 1992
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On rank-revealing factorisations
S. Chandrasekaran and I. C. F. Ipsen · 1994
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Machine learning, neural and statistical classification
D. Michie, D. J. Spiegelhalter, and C. C. Taylor · 1994
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Efficient algorithms for computing a strong rank-revealing QR factorization
M. Gu and S. C. Eisenstat · 1996
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Four algorithms for the the efficient computation of truncated pivoted QR approximations to a sparse matrix
G. W. Stewart · 1999
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Incomplete cross approximation in the mosaic-skeleton method
E. E. Tyrtyshnikov · 2000
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Using the Nyström method to speed up kernel machines
C. Williams and M. Seeger · 2001
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Vector algebra in the analysis of genome-wide expression data
F. G. Kuruvilla, P. J. Park, and S. L. Schreiber · 2002
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Generalized Inverses: Theory and Applications. Second Edition
A. Ben-Israel and T. N. E. Greville · 2003
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Pass-efficient algorithms for approximating large matrices
P. Drineas and R. Kannan · 2003
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Spectral grouping using the Nyström method
C. Fowlkes, S. Belongie, F. Chung, and J. Malik · 2004
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Fast Monte Carlo algorithms for finding low-rank approximations
A. Frieze, R. Kannan, and S. Vempala · 2004
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Result analysis of the NIPS 2003 feature selection challenge
I. Guyon, S. Gunn, A. Ben-Hur, and G. Dror · 2004
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Algorithm 844: computing sparse reduced-rank approximations to sparse matrices
M. W. Berry, S. A. Pulatova, and G. W. Stewart · 2005
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On the Nyström method for approximating a gram matrix for improved kernel-based learning
P. Drineas and M. W. Mahoney · 2005
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Matrix approximation and projective clustering via volume sampling
A. Deshpande, L. Rademacher, S. Vempala, and G. Wang · 2006
Efficient volume sampling for row/column subset selection
A. Deshpande and L. Rademacher · 2010
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UCI machine learning repository, 2010
A. Frank and A. Asuncion · 2010
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Making large-scale Nyström approximation possible
M. Li, J. T. Kwok, and B.-L. Lu · 2010
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Matrix coherence and the Nyström method
A. Talwalkar and A. Rostamizadeh · 2010
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Clustered Nyström method for large scale manifold learning and dimension reduction
K. Zhang and J. T. Kwok · 2010
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Fast Monte Carlo algorithms for matrices III: computing a compressed approximate matrix decomposition
P. Drineas, R. Kannan, and M. W. Mahoney · 2006
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Relative-error CUR matrix decompositions
P. Drineas, M. W. Mahoney, and S. Muthukrishnan · 2008
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Tensor-CUR decompositions for tensor-based data
M. W. Mahoney, M. Maggioni, and P. Drineas · 2008
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Large-scale manifold learning
A. Talwalkar, S. Kumar, and H. Rowley · 2008
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Improved Nyström low-rank approximation and error analysis
K. Zhang, I. W. Tsang, and J. T. Kwok · 2008
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Modeling wine preferences by data mining from physicochemical properties
P. Cortez, A. Cerdeira, F. Almeida, T. Matos, and J. Reis · 2009
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C. Boutsidis, P. Drineas, and M. Magdon-Ismail · 2011
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Finding structure with randomness: probabilistic algorithms for constructing approximate matrix decompositions
N. Halko, P.-G. Martinsson, and J. A. Tropp · 2011
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Improved bound for the Nyström method and its application to kernel classification
R. Jin, T. Yang, and M. Mahdavi · 2011
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Divide-and-conquer matrix factorization
L. Mackey, A. Talwalkar, and M. I. Jordan · 2011
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Randomized algorithms for matrices and data
M. W. Mahoney · 2011
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Active learning using on-line algorithms
C. Mesterharm and M. J. Pazzani · 2011
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Fast approximation of matrix coherence and statistical leverage
P. Drineas, M. Magdon-Ismail, M. W. Mahoney, and D. P. Woodruff · 2012
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Optimal column-based low-rank matrix reconstruction
V. Guruswami and A. K. Sinop · 2012
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Sampling methods for the Nyström method
S. Kumar, M. Mohri, and A. Talwalkar · 2012
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Revisiting the Nyström method for improved large-scale machine learning
A. Gittens and M. W. Mahoney · 2013
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