9 papers
Counterfactually Fair Regression via Optimal Transport
M. Generali Lince, S. Gaucher, J-J. Vie +1
We consider the problem of learning a counterfactually fair regressor. We adopt a causal uncertainty view in which counterfactual fairness is defined with resampled noise. We focus…
Geometry of Relaxed Fair Regression: A Unified Framework for Aware and Unaware Settings
M. Generali Lince, V. Divol, R. Flamary +2
Fairness-accuracy trade-offs are a central concern in the deployment of fairness-aware machine learning methods. When sensitive attributes are unavailable at inference time-the so…
Complexity of Auctions with Interdependence
Patrick Loiseau, Simon Mauras, Minrui Xu
We study auction design in the celebrated interdependence model introduced by Milgrom and Weber [1982], where a mechanism designer allocates a good, maximizing the value of the age…
On the Impact of the Utility in Semivalue-based Data Valuation
Mélissa Tamine, Benjamin Heymann, Maxime Vono +1
Semivalue-based data valuation uses cooperative-game theory intuitions to assign each data point a value reflecting its contribution to a downstream task. Still, those values depen…
Correlation of Rankings in Matching Markets
Rémi Castera, Patrick Loiseau, Bary S. R. Pradelski
We study the role of correlation in matching markets, where multiple decision-makers simultaneously face selection problems from the same pool of candidates. We propose a model in…
The Price of Opportunity Fairness in Matroid Allocation Problems
Rémi Castera, Felipe Garrido-Lucero, Patrick Loiseau +3
We consider matroid allocation problems under opportunity fairness constraints: resources need to be allocated to a set of agents under matroid constraints (which include classical…