A Note On Spectral Clustering

ESA, 2016.

Cited by: 4|Views10
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Abstract:

Spectral clustering is a popular and successful approach for partitioning the nodes of a graph into clusters for which the ratio of outside connections compared to the volume (sum of degrees) is small. In order to partition into $k$ clusters, one first computes an approximation of the first $k$ eigenvectors of the (normalized) Laplacian...More

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