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Community detection in sparse latent space models

2020-08-04 · Fengnan Gao, Zongming Ma, Hongsong Yuan

We show that a simple community detection algorithm originated from stochastic blockmodel literature achieves consistency, and even optimality, for a broad and flexible class of sparse latent space models. The class of models includes latent eigenmodels (arXiv:0711.1146). The community detection algorithm is based on spectral clustering followed by local refinement via normalized edge counting.

📄 PDF Abstract BibTeX arXiv:2008.01375

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ClusteringCommunity Detection

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Spectral Clustering Spectral clustering has attracted increasing attention due to the promising ability in dealing with nonlinearly separable datasets [15], [16]. In spectral clustering, the…

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