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» Spectral clustering based on matrix perturbation theory
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CHINAF
2007
73views more  CHINAF 2007»
13 years 4 months ago
Spectral clustering based on matrix perturbation theory
Zheng Tian, XiaoBin Li, YanWei Ju
NIPS
2008
13 years 6 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»
13 years 4 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
SIGPRO
2010
122views more  SIGPRO 2010»
13 years 2 months ago
Parameter estimation for exponential sums by approximate Prony method
The recovery of signal parameters from noisy sampled data is a fundamental problem in digital signal processing. In this paper, we consider the following spectral analysis problem...
Daniel Potts, Manfred Tasche
NIPS
2004
13 years 6 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...