no code implementations • 3 Jul 2023 • Danele Lunghi, Alkis Simitsis, Olivier Caelen, Gianluca Bontempi
Although early results of adversarial machine learning indicate the huge potential of the approach to specific domains such as image processing, still there is a gap in both the research literature and practice regarding how to generalize adversarial techniques in other domains and applications.
1 code implementation • 3 Sep 2019 • Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Liyun He-Guelton, Olivier Caelen, Michael Granitzer, Sylvie Calabretto
Our multiple perspectives HMM-based approach offers automated feature engineering to model temporal correlations so as to improve the effectiveness of the classification task and allows for an increase in the detection of fraudulent transactions when combined with the state of the art expert based feature engineering strategy for credit card fraud detection.
1 code implementation • 15 May 2019 • Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Olivier Caelen, Liyun He-Guelton, Sylvie Calabretto, Michael Granitzer
In this article, we model a sequence of credit card transactions from three different perspectives, namely (i) does the sequence contain a Fraud?
no code implementations • 20 Apr 2018 • Fabirzio Carcillo, Yann-Aël Le Borgne, Olivier Caelen, Gianluca Bontempi
An adequate selection of the set of cardholders is therefore crucial for an efficient fraud detection process.