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Novelty detection with multivariate extreme value theory, part I: A numerical approach to multimodal estimation

Abstract:

Extreme Value Theory (EVT) describes the distribution of data considered extreme with respect to some generative distribution, effectively modelling the tails of that distribution. In novelty detection, or one-class classification, we wish to determine if data are "normal" with respect to some model of normality. If that model consists of generative distributions, then EVT is appropriate for describing the behaviour of extremes generated from the model, and can be used to determine the locati...

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Publisher copy:
10.1109/MLSP.2009.5306231

Authors


Clifton, DA More by this author
Hugueny, S More by this author
Tarassenko, L More by this author
Journal:
Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009
Publication date:
2009
DOI:
URN:
uuid:83b0f9ba-daa6-41dc-8ec1-4ea2e9c39ab7
Source identifiers:
298767
Local pid:
pubs:298767
Language:
English

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