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Recent years have witnessed intense development of randomized methods for low-rank approximation.
Estimation of principal components and related models by iterative least squares
Herman Wold. 1966 · 1966
Earlier work this paper cites.
Estimating the largest eigenvalue by the power and Lanczos algorithms with a random start
Jacek Kuczyński and Henryk Woźniakowski. 1992 · 1992
Earlier work this paper cites.
ARPACK User’s Guide: Solution of Large-Scale Eigenvalue Problems with Implicitly Restarted Arnoldi Methods
Richard Lehoucq, Daniel Sorensen, and Chao Yang. 1998 · 1998
Earlier work this paper cites.
LAPACK User’s Guide
Edward Anderson, Zhaojun Bai, Christian Bischof, Laura Susan Blackford, James Demmel, Jack Dongarra, Jeremy Du Croz, Anne Greenbaum, Sven Hammarling, Alan McKenney, and Daniel Sorensen. 1999 · 1999
Earlier work this paper cites.
Combining implicit restart and partial reorthogonalization in Lanczos bidiagonalization. Presentation at U.C. Berkeley, sponsored by Stanford’s Scientific Computing and Computational Mathematics (succeeded by the Institute for Computational and Mathematical Engineering)
Rasmus Larsen. 2001 · 2001
Earlier work this paper cites.
ATIS Telecom Glossary, American National Standard T1.523
Alliance for Telecommunications Industry Solutions Committee PRQC. 2011 · 2011
Cited alongside, same era.
The University of Florida sparse matrix collection
Timothy A. Davis and Yifan Hu. 2011 · 2011
Cited alongside, same era.
Finding structure with randomness: probabilistic algorithms for constructing approximate matrix decompositions
Nathan Halko, Per-Gunnar Martinsson, and Joel Tropp. 2011 · 2011
Cited alongside, same era.
Matrix Computations
Gene Golub and Charles Van Loan. 2012 · 2012
Cited alongside, same era.
Randomized LU decomposition
Gil Shabat, Yaniv Shmueli, and Amir Averbuch. 2013 · 2013
Cited alongside, same era.
LibSkylark: Sketching-Based Matrix Computations for Machine Learning
Haim Avron, Costas Bekas, Christos Boutsidis, Kenneth Clarkson, Prabhanjan Kambadur, Giorgos Kollias, Michael Mahoney, Ilse Ipsen, Yves Ineichen, Vikas Sindhwani, and David Woodruff. 2014 · 2014
Closest in time.
Memory-efficient PCA approaches for large-group ICA. (2014)
Srinivas Rachakonda, Rogers F. Silva, Jingyu Liu, and Vince Calhoun. 2014 · 2014
Closest in time.
Randomized algorithms for low-rank matrix factorizations: sharp performance bounds
Rafi Witten and Emmanuel Candès. 2014 · 2014
Closest in time.
Sketching as a Tool for Numerical Linear Algebra
David Woodruff. 2014 · 2014
Closest in time.
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