Spectral CUSUM for Online Network Structure Change Detection

• URL: http://arxiv.org/abs/1910.09083v8
• Date: Thu, 16 Mar 2023 16:54:32 GMT
• Title: Spectral CUSUM for Online Network Structure Change Detection
• Authors: Minghe Zhang, Liyan Xie, Yao Xie
• Abstract summary: This paper presents an online change detection algorithm called Spectral-CUSUM to detect unknown network structure changes. We characterize the average run length (ARL) and the expected detection delay (EDD) of the Spectral-CUSUM procedure and prove its optimality.
• Score: 14.525631550607281
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Detecting abrupt changes in the community structure of a network from noisy observations is a fundamental problem in statistics and machine learning. This paper presents an online change detection algorithm called Spectral-CUSUM to detect unknown network structure changes through a generalized likelihood ratio statistic. We characterize the average run length (ARL) and the expected detection delay (EDD) of the Spectral-CUSUM procedure and prove its asymptotic optimality. Finally, we demonstrate the good performance of the Spectral-CUSUM procedure and compare it with several baseline methods using simulations and real data examples on seismic event detection using sensor network data.

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