3 papers
cs.LG2024
Debiasing Machine Learning Models by Using Weakly Supervised Learning
Renan D. B. Brotto, Jean-Michel Loubes, Laurent Risser +3
We tackle the problem of bias mitigation of algorithmic decisions in a setting where both the output of the algorithm and the sensitive variable are continuous. Most of prior work…
cs.CL2023
Are fairness metric scores enough to assess discrimination biases in machine learning?
Fanny Jourdan, Laurent Risser, Jean-Michel Loubes +1
This paper presents novel experiments shedding light on the shortcomings of current metrics for assessing biases of gender discrimination made by machine learning algorithms on tex…
cs.LG2023
How optimal transport can tackle gender biases in multi-class neural-network classifiers for job recommendations?
Fanny Jourdan, Titon Tshiongo Kaninku, Nicholas Asher +2
Automatic recommendation systems based on deep neural networks have become extremely popular during the last decade. Some of these systems can however be used for applications whic…