Spectral clustering

In multivariate statistics and the clustering of data, spectral clustering techniques make use of the spectrum (eigenvalues) of the similarity matrix… (More)
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Topic mentions per year

1989-2018
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Highly Cited
2011
Highly Cited
2011
Spectral clustering algorithms have been shown to be more effective in finding clusters than some traditional algorithms, such as… (More)
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Highly Cited
2011
Highly Cited
2011
In many clustering problems, we have access to multiple view s of the data each of which could be individually used for… (More)
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Highly Cited
2009
Highly Cited
2009
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data… (More)
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Highly Cited
2005
Highly Cited
2005
Clustering nodes in a graph is a useful general technique in data mining of large network data sets. In this context, Newman and… (More)
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Highly Cited
2004
Highly Cited
2004
We study a number of open issues in spectral clustering: (i) Selecting the appropriate scale of analysis, (ii) Handling multi… (More)
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Highly Cited
2004
Highly Cited
2004
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space… (More)
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Highly Cited
2004
Highly Cited
2004
  • Ulrike von Luxburg, Mikhail Belkin
  • 2004
Consistency is a key property of all statistical procedures analyzing randomly sampled data. Surprisingly, despite decades of… (More)
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Highly Cited
2003
Highly Cited
2003
Spectral clustering refers to a class of techniques which rely on the eigenstructure of a similarity matrix to partition points… (More)
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Highly Cited
2003
Highly Cited
2003
We propose a principled account on multiclass spectral clustering. Given a discrete clustering formulation, we first solve a… (More)
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Highly Cited
2001
Highly Cited
2001
Yair Weiss School of CS & Engr. The Hebrew Univ. yweiss@cs.huji.ac.il Despite many empirical successes of spectral clustering… (More)
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