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Nyström method
Known as:
Nystroem method
, Nystrom method
In numerical analysis, the Nyström method or quadrature method seeks the numerical solution of an integral equation by replacing the integral with a…
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Related topics
Related topics
8 relations
Gaussian quadrature
List of numerical analysis topics
Low Rank Matrix Approximations
Numerical analysis
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Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2018
Highly Cited
2018
Massively scalable Sinkhorn distances via the Nyström method
Jason M. Altschuler
,
F. Bach
,
Alessandro Rudi
,
J. Weed
Neural Information Processing Systems
2018
Corpus ID: 55582419
The Sinkhorn "distance", a variant of the Wasserstein distance with entropic regularization, is an increasingly popular tool in…
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Highly Cited
2016
Highly Cited
2016
Recursive Sampling for the Nystrom Method
Cameron Musco
,
C. Musco
Neural Information Processing Systems
2016
Corpus ID: 11918471
We give the first algorithm for kernel Nystr\"om approximation that runs in *linear time in the number of training points* and is…
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Highly Cited
2013
Highly Cited
2013
Revisiting the Nystrom Method for Improved Large-scale Machine Learning
Alex Gittens
,
Michael W. Mahoney
Journal of machine learning research
2013
Corpus ID: 13109232
We reconsider randomized algorithms for the low-rank approximation of SPSD matrices such as Laplacian and kernel matrices that…
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Highly Cited
2013
Highly Cited
2013
Improving CUR matrix decomposition and the Nyström approximation via adaptive sampling
Shusen Wang
,
Zhihua Zhang
Journal of machine learning research
2013
Corpus ID: 6204627
The CUR matrix decomposition and the Nystrom approximation are two important low-rank matrix approximation techniques. The…
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Highly Cited
2012
Highly Cited
2012
Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison
Tianbao Yang
,
Yu-Feng Li
,
M. Mahdavi
,
Rong Jin
,
Zhi-Hua Zhou
Neural Information Processing Systems
2012
Corpus ID: 1830773
Both random Fourier features and the Nystrom method have been successfully applied to efficient kernel learning. In this work, we…
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Review
2010
Review
2010
Dimension Reduction: A Guided Tour
C. Burges
Found. Trends Mach. Learn.
2010
Corpus ID: 49803104
We give a tutorial overview of several geometric methods for dimension reduction. We divide the methods into projective methods…
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Highly Cited
2009
Highly Cited
2009
Ensemble Nystrom Method
Sanjiv Kumar
,
M. Mohri
,
Ameet Talwalkar
Neural Information Processing Systems
2009
Corpus ID: 446764
A crucial technique for scaling kernel methods to very large data sets reaching or exceeding millions of instances is based on…
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Highly Cited
2007
Highly Cited
2007
Semi-Supervised Graph-Based Hyperspectral Image Classification
Gustau Camps-Valls
,
T. Marsheva
,
Dengyong Zhou
IEEE Transactions on Geoscience and Remote…
2007
Corpus ID: 15106876
This paper presents a semi-supervised graph-based method for the classification of hyperspectral images. The method is designed…
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Highly Cited
2000
Highly Cited
2000
Using the Nyström Method to Speed Up Kernel Machines
Christopher K. I. Williams
,
M. Seeger
Neural Information Processing Systems
2000
Corpus ID: 42041158
A major problem for kernel-based predictors (such as Support Vector Machines and Gaussian processes) is that the amount of…
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Highly Cited
1990
Highly Cited
1990
A Nyström method for boundary integral equations in domains with corners
R. Kress
1990
Corpus ID: 54927829
SummaryWe give a convergence and error analysis for a Nyström method on a graded mesh for the numerical solution of boundary…
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