# Neighborhood Component Analysis (Renaud Rivier, University of Geneva)

03.06.2019 17:00

Statistical learning is an interesting field in theoretical and applied mathematics; it combines ideas from geometry, probability theory and computer science (among others). In this talk, I would like to present a practical "data mining" challenge I worked on and some ideas that were very helpful in solving it - or at least in getting interesting results.

I will first briefly introduced statistical learning theory and present a few well-known algorithms. I will then move to a particular problem of fraud detection where classical algorithms fail to perform well. Finally I will talk about the idea of metric learning, present the method called "Neighborhood Component Analysis" and show how it could be used in the particular case of fraud detection.

### Lieu

Room 17, Séminaire des doctorants

### Organisé par

Section de mathématiques### Intervenants

Renaud Rivier, University of Genevaentrée libre

### Plus d'infos

Contact: *missing email*