Spectral subgraph detection with corrupt observations

  title={Spectral subgraph detection with corrupt observations},
  author={Benjamin A. Miller and Nicholas Arcolano},
  journal={2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
Recent work on signal detection in graph-based data focuses on classical detection when the signal and noise are both in the form of discrete entities and their relationships. In practice, the relationships of interest may not be directly observable, or may be observed through a noisy mechanism. The effects of imperfect observations add another layer of difficulty to the detection problem, beyond the effects of typical random fluctuations in the background graph. This paper analyzes the impact… CONTINUE READING