A comparative evaluation of novelty detection algorithms for discrete sequences

Autor: Domingues, Rémi, Michiardi, Pietro, Barlet, Jérémie, Filippone, Maurizio

Publikováno v: Artificial Intelligence Review (2019)

The identification of anomalies in temporal data is a core component of numerous research areas such as intrusion detection, fault prevention, genomics and fraud detection. This article provides an experimental comparison of the novelty detection pro

Externí odkaz: http://arxiv.org/abs/1902.10940

A comparative evaluation of outlier detection algorithms: Experiments and analyses

Autor: Domingues, Rémi, Filippone, Maurizio, Michiardi, Pietro, Zouaoui, Jihane

Publikováno v: In Pattern Recognition February 2018 74:406-421

Deep Gaussian process autoencoders for novelty detection

Autor: Domingues, Rémi, Michiardi, Pietro, Zouaoui, Jihane, Filippone, Maurizio

Publikováno v: Machine Learning, June 2018, Special Issue of the ECML PKDD 2018 Journal Track, ISSN: 0885-6125

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1093::7139b0bbf8723b058b206ceea47636f5
http://www.eurecom.fr/publication/5589

An application of unsupervised fraud detection to Passenger Name Records

Autor: Domingues, Rémi, Buonora, Francesco, Senesi, Romain, Thonnard, Olivier

Publikováno v: RSDA 2016, 3rd IEEE International Workshop on Reliability and Security Data Analysis, co-located with DSN 2016, 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshop, June 28th-July 1st, 2016, Toulouse, France

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1093::80da9cee9e68efc8f820b819730f3459
http://www.eurecom.fr/publication/5058