5 papers
Demographic Parity Tails for Regression
Naht Sinh Le, Christophe Denis, Mohamed Hebiri
Demographic parity (DP) is a widely studied fairness criterion in regression, enforcing independence between the predictions and sensitive attributes. However, constraining the ent…
Fair regression under localized demographic parity constraints
Arthur Charpentier, Christophe Denis, Romuald Elie +2
Demographic parity (DP) is a widely used group fairness criterion requiring predictive distributions to be invariant across sensitive groups. While natural in classification, full…
Fairness Meets Privacy: Integrating Differential Privacy and Demographic Parity in Multi-class Classification
Lilian Say, Christophe Denis, Rafael Pinot
The increasing use of machine learning in sensitive applications demands algorithms that simultaneously preserve data privacy and ensure fairness across potentially sensitive sub-p…
Set to Be Fair: Demographic Parity Constraints for Set-Valued Classification
Eyal Cohen, Christophe Denis, Mohamed Hebiri
Set-valued classification is used in multiclass settings where confusion between classes can occur and lead to misleading predictions. However, its application may amplify discrimi…
Empirical risk minimization algorithm for multiclass classification of S.D.E. paths
Christophe Denis, Eddy Ella Mintsa
We address the multiclass classification problem for stochastic diffusion paths, assuming that the classes are distinguished by their drift functions, while the diffusion coefficie…