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Optimal Laplacian regularization for sparse spectral community detection

2019-12-03 · Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay

Regularization of the classical Laplacian matrices was empirically shown to improve spectral clustering in sparse networks. It was observed that small regularizations are preferable, but this point was left as a heuristic argument. In this paper we formally determine a proper regularization which is intimately related to alternative state-of-the-art spectral techniques for sparse graphs.

📄 PDF Abstract BibTeX arXiv:1912.01419

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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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