Online Community Detection by Spectral Cusum

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 Gaus-sian model setting. Theoretical analysis is provided to char-acterize 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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