9 citations · 9 across the 1 of their papers we have counts for
5 papers
A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set
Philippe Besse, Eustasio del Barrio, Paula Gordaliza +2
Applications based on Machine Learning models have now become an indispensable part of the everyday life and the professional world. A critical question then recently arised among…
Wikistat 2.0: Educational Resources for Artificial Intelligence
Philippe Besse, Brendan Guillouet, Béatrice Laurent
Big data, data science, deep learning, artificial intelligence are the key words of intense hype related with a job market in full evolution, that impose to adapt the contents of o…
Can everyday AI be ethical. Fairness of Machine Learning Algorithms
Philippe Besse, Celine Castets-Renard, Aurelien Garivier +1
Combining big data and machine learning algorithms, the power of automatic decision tools induces as much hope as fear. Many recently enacted European legislation (GDPR) and French…
Confidence Intervals for Testing Disparate Impact in Fair Learning
Philippe Besse, Eustasio del Barrio, Paula Gordaliza +1
We provide the asymptotic distribution of the major indexes used in the statistical literature to quantify disparate treatment in machine learning. We aim at promoting the use of c…
Destination Prediction by Trajectory Distribution Based Model
Philippe C. Besse, Brendan Guillouet, Jean-Michel Loubes +1
In this paper we propose a new method to predict the final destination of vehicle trips based on their initial partial trajectories. We first review how we obtained clustering of t…