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» Spectral Clustering with Perturbed Data
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NIPS
2008
12 years 3 months ago
Spectral Clustering with Perturbed Data
Spectral clustering is useful for a wide-ranging set of applications in areas such as biological data analysis, image processing and data mining. However, the computational and/or...
Ling Huang, Donghui Yan, Michael I. Jordan, Nina T...
CORR
2010
Springer
249views Education» more  CORR 2010»
12 years 1 months ago
Performance Analysis of Spectral Clustering on Compressed, Incomplete and Inaccurate Measurements
Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged a...
Blake Hunter, Thomas Strohmer
NIPS
2004
12 years 3 months ago
Limits of Spectral Clustering
An important aspect of clustering algorithms is whether the partitions constructed on finite samples converge to a useful clustering of the whole data space as the sample size inc...
Ulrike von Luxburg, Olivier Bousquet, Mikhail Belk...
CHINAF
2007
73views more  CHINAF 2007»
12 years 1 months ago
Spectral clustering based on matrix perturbation theory
Zheng Tian, XiaoBin Li, YanWei Ju
ECML
2006
Springer
12 years 5 months ago
Fast Spectral Clustering of Data Using Sequential Matrix Compression
Spectral clustering has attracted much research interest in recent years since it can yield impressively good clustering results. Traditional spectral clustering algorithms first s...
Bo Chen, Bin Gao, Tie-Yan Liu, Yu-Fu Chen, Wei-Yin...
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