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Kernel k-means: spectral clustering and normalized cuts

KDD, pp.551-556, (2004)

Cited by: 1208|Views183
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Abstract

Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have remained only loosely related. In this paper, we give an explicit theoretical connection between them. We show the generality of the weighted kernel k-means object...More

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Inderjit S. Dhillon
Inderjit S. Dhillon
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