An Extreme Function Theory for Novelty Detection

@article{Clifton2013AnEF,
  title={An Extreme Function Theory for Novelty Detection},
  author={David A. Clifton and Lei A. Clifton and Samuel Hugueny and David Wong and Lionel Tarassenko},
  journal={IEEE Journal of Selected Topics in Signal Processing},
  year={2013},
  volume={7},
  pages={28-37}
}
We introduce an extreme function theory as a novel method by which probabilistic novelty detection may be performed with functions, where the functions are represented by time-series of (potentially multivariate) discrete observations. We set the method within the framework of Gaussian processes (GP), which offers a convenient means of constructing a distribution over functions. Whereas conventional novelty detection methods aim to identify individually extreme data points, with respect to a… CONTINUE READING

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