Credit card fraud detection is a challenging task since fraudulent actions are hidden in
massive legitimate behaviors. This work aims to learn a new representation for each …

Success in supervised learning is constrained by availability of an adequate labeled data
sample for training. The problem of a complete labeling of every data of the training dataset …

Alpha integration is a family of integrators that encompasses many classic fusion operators
(eg, mean, product, minimum, maximum) as particular cases. This paper proposes vector …

Automatic data fusion is an important field of machine learning that has been increasingly
studied. The objective is to improve the classification performance from several individual …

The essential step of surrogating algorithms is phase randomizing the Fourier transform
while preserving the original spectrum amplitude before computing the inverse Fourier …

In this paper, several methods based on signal processing on graphs are proposed to
improve the performance of credit card fraud detection. The proposed methods consist of a …

Purpose This research aims to study the effect of R&D (research and development) enablers
and barriers as well as industrial property on exploration, their influence on exploitation and …

Independent component analysis (ICA) is a blind source separation technique where data
are modeled as linear combinations of several independent non-Gaussian sources. The …

This paper presents a theoretical comparison of early and late fusion methods. An initial
discussion on the conditions to apply early or late (soft or hard) fusion is introduced. The …

This paper presents a signal processing framework for the problem of automatic credit card
fraud detection. This is a critical problem affecting large financial companies that has …