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Online Community Detection by Spectral CUSUM

20 October 2019
Minghe Zhang
Liyan Xie
Yao Xie
ArXiv (abs)PDFHTML
Abstract

We present an online community change detection algorithm called spectral CUSUM to detect the emergence of a community using a subspace projection procedure based on a Gaussian model setting. Theoretical analysis is provided to characterize the average run length (ARL) and expected detection delay (EDD), as well as the asymptotic optimality. Simulation and real data examples demonstrate the good performance of the proposed method.

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