Fetching the paper…
Reading the bibliography…
Matrix operations such as matrix inversion, eigenvalue decomposition, singular value decomposition are ubiquitous in real-world applications.
Über die praktische auflösung von integralgleichungen mit anwendungen auf randwertaufgaben
Evert J. Nyström · 1930
Earlier work this paper cites.
Extensions of Lipschitz mappings into a Hilbert space
William B. Johnson and Joram Lindenstrauss · 1984
Earlier work this paper cites.
Four algorithms for the efficient computation of truncated pivoted QR approximations to a sparse matrix
G. W. Stewart · 1999
Earlier work this paper cites.
Using the Nyström method to speed up kernel machines
Christopher Williams and Matthias Seeger · 2001
Earlier work this paper cites.
Generalized Inverses: Theory and Applications. Second Edition
Adi Ben-Israel and Thomas N.E. Greville · 2003
Earlier work this paper cites.
Finding frequent items in data streams
Moses Charikar, Kevin Chen, and Martin Farach-Colton · 2004
Earlier work this paper cites.
Spectral grouping using the Nyström method
Charless Fowlkes, Serge Belongie, Fan Chung, and Jitendra Malik · 2004
Earlier work this paper cites.
Subgradient and sampling algorithms for l1 regression
Kenneth L Clarkson · 2005
Earlier work this paper cites.
Random features for large-scale kernel machines
Ali Rahimi and Benjamin Recht · 2007
Earlier work this paper cites.
Clustered Nyström method for large scale manifold learning and dimension reduction
Kai Zhang and James T. Kwok · 2010
Earlier work this paper cites.
The spectral norm error of the naive Nyström extension
Alex Gittens · 2011
Earlier work this paper cites.
Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
Nathan Halko, Per-Gunnar Martinsson, and Joel A. Tropp · 2011
Earlier work this paper cites.
Randomized algorithms for matrices and data
Michael W. Mahoney · 2011
Cited alongside, same era.
Numerical methods for large eigenvalue problems
Yousef Saad · 2011
Cited alongside, same era.
Tabulation-based 5-independent hashing with applications to linear probing and second moment estimation
Mikkel Thorup and Yin Zhang · 2012
Cited alongside, same era.
Nyström method vs random fourier features: A theoretical and empirical comparison
Tianbao Yang, Yu-Feng Li, Mehrdad Mahdavi, Rong Jin, and Zhi-Hua Zhou · 2012
Cited alongside, same era.
Low rank approximation and regression in input sparsity time
Kenneth L. Clarkson and David P. Woodruff · 2013
Cited alongside, same era.
The fast cauchy transform and faster robust linear regression
Kenneth L Clarkson, Petros Drineas, Malik Magdon-Ismail, Michael W Mahoney, Xiangrui Meng, and David P Woodruff · 2013
Near-optimal column-based matrix reconstruction
Christos Boutsidis, Petros Drineas, and Malik Magdon-Ismail · 2014
Later among the works it cites.
ℓ p \ell_{p} row sampling by lewis weights
Michael B Cohen and Richard Peng · 2014
Later among the works it cites.
Scalable kernel methods via doubly stochastic gradients
Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina F Balcan, and Le Song · 2014
Later among the works it cites.
Lsrn: A parallel iterative solver for strongly over-or underdetermined systems
Xiangrui Meng, Michael A Saunders, and Michael W Mahoney · 2014
Later among the works it cites.
Memory efficient kernel approximation
Si Si, Cho-Jui Hsieh, and Inderjit Dhillon · 2014
Later among the works it cites.
Spsd matrix approximation via column selection: Theories, algorithms, and extensions
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Turning big data into tiny data: Constant-size coresets for k-means, pca and projective clustering
Dan Feldman, Melanie Schmidt, and Christian Sohler · 2013
Cited alongside, same era.
Revisiting the nyström method for improved large-scale machine learning
Alex Gittens and Michael W. Mahoney · 2013
Cited alongside, same era.
Low-distortion subspace embeddings in input-sparsity time and applications to robust linear regression
Xiangrui Meng and Michael W Mahoney · 2013
Cited alongside, same era.
Fast and scalable polynomial kernels via explicit feature maps
Ninh Pham and Rasmus Pagh · 2013
Cited alongside, same era.
Improving CUR matrix decomposition and the Nyström approximation via adaptive sampling
Shusen Wang and Zhihua Zhang · 2013
Cited alongside, same era.
Structured block basis factorization for scalable kernel matrix evaluation
Ruoxi Wang, Yingzhou Li, Michael W Mahoney, and Eric Darve
Cited in the paper.
Shusen Wang, Luo Luo, and Zhihua Zhang · 2014
Later among the works it cites.
Sketching as a tool for numerical linear algebra
David P Woodruff · 2014
Later among the works it cites.
Communication-optimal distributed principal component analysis in the column-partition model
Christos Boutsidis and David P Woodruff · 2015
Closest in time.
Stronger approximate singular value decomposition via the block Lanczos and power methods
Cameron Musco and Christopher Musco · 2015
Closest in time.
An introduction to matrix concentration inequalities
Joel A Tropp · 2015
Closest in time.
Kernel interpolation for scalable structured gaussian processes (kiss-gp)
Andrew Gordon Wilson and Hannes Nickisch · 2015
Closest in time.