Approximate Spectral Clustering: Efficiency and Guarantees

arXiv: Discrete Mathematics, 2015.

Cited by: 12|Views5

Abstract:

Approximate Spectral Clustering (ASC) is a popular and successful heuristic for partitioning the nodes of a graph $G$ into clusters for which the ratio of outside connections compared to the volume (sum of degrees) is small. ASC consists of the following two subroutines: i) compute an approximate Spectral Embedding via the Power method; a...More

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