@inproceedings{8d35bdf154e54447a4fd78be46053d8e,
title = "Toward matched filter optimization for subgraph detection in dynamic networks",
abstract = "This paper outlines techniques for optimization of filter coefficients in a spectral framework for anomalous subgraph detection. Restricting the scope to the detection of a known signal in i.i.d. noise, the optimal coefficients for maximizing the signal's power are shown to be found via a rank-1 tensor approximation of the subgraph's dynamic topology. While this technique optimizes our power metric, a filter based on average degree is shown in simulation to work nearly as well in terms of power maximization and detection performance, and better separates the signal from the noise in the eigenspace.",
keywords = "community detection, dynamic graphs, graph algorithms, matched filtering, signal detection theory",
author = "Miller, {Benjamin A.} and Bliss, {Nadya T.}",
year = "2012",
month = nov,
day = "6",
doi = "10.1109/SSP.2012.6319635",
language = "English (US)",
isbn = "9781467301831",
series = "2012 IEEE Statistical Signal Processing Workshop, SSP 2012",
pages = "113--116",
booktitle = "2012 IEEE Statistical Signal Processing Workshop, SSP 2012",
note = "2012 IEEE Statistical Signal Processing Workshop, SSP 2012 ; Conference date: 05-08-2012 Through 08-08-2012",
}