@inproceedings{8fab63a690634fe99c01035486bd4eef,
title = "White functionals for anomaly detection in dynamical systems",
abstract = "We propose new methodologies to detect anomalies in discrete-time processes taking values in a probability space. These methods are based on the inference of functionals whose evaluations on successive states visited by the process are stationary and have low autocorrelations. Deviations from this behavior are used to flag anomalies. The candidate functionals are estimated in a subspace of a reproducing kernel Hilbert space associated with the original probability space considered. We provide experimental results on simulated datasets which show that these techniques compare favorably with other algorithms.",
author = "Marco Cuturi and Vert, \{Jean Philippe\} and Alexandre D'Aspremont",
year = "2009",
month = jan,
day = "1",
language = "English",
isbn = "9781615679119",
series = "Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference",
publisher = "Neural Information Processing Systems",
pages = "432--440",
booktitle = "Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference",
note = "23rd Annual Conference on Neural Information Processing Systems, NIPS 2009 ; Conference date: 07-12-2009 Through 10-12-2009",
}