Lecture

Network clustering

Description

This lecture covers network clustering using unnormalized spectral clustering and k-means algorithm. It explains the process of clustering points in a graph, defining similarity measures, and the k-means clustering algorithm. The properties of eigenvalues in graph Laplacians, estimating the block model, and measuring structural similarity are also discussed.

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