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 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.
| Original language | English (US) |
|---|---|
| Title of host publication | 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 3402-3406 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781509066315 |
| DOIs | |
| State | Published - May 2020 |
| Externally published | Yes |
| Event | 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Barcelona, Spain Duration: May 4 2020 → May 8 2020 |
Publication series
| Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
|---|---|
| Volume | 2020-May |
| ISSN (Print) | 1520-6149 |
Conference
| Conference | 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 |
|---|---|
| Country/Territory | Spain |
| City | Barcelona |
| Period | 5/4/20 → 5/8/20 |
Bibliographical note
Publisher Copyright:© 2020 IEEE.
Keywords
- Community detection
- online change-point detection
- spectral method