34 citations · 171 across the 39 of their papers we have counts for
4 papers · 1 filter
Bounding and Approximating Intersectional Fairness through Marginal Fairness
Mathieu Molina, Patrick Loiseau
Discrimination in machine learning often arises along multiple dimensions (a.k.a. protected attributes); it is then desirable to ensure \emph{intersectional fairness} -- i.e., that…
Fairness in Selection Problems with Strategic Candidates
Vitalii Emelianov, Nicolas Gast, Patrick Loiseau
To better understand discriminations and the effect of affirmative actions in selection problems (e.g., college admission or hiring), a recent line of research proposed a model bas…
Pareto-Optimal Fairness-Utility Amortizations in Rankings with a DBN Exposure Model
Till Kletti, Jean-Michel Renders, Patrick Loiseau
In recent years, it has become clear that rankings delivered in many areas need not only be useful to the users but also respect fairness of exposure for the item producers. We con…
Introducing the Expohedron for Efficient Pareto-optimal Fairness-Utility Amortizations in Repeated Rankings
Till Kletti, Jean-Michel Renders, Patrick Loiseau
We consider the problem of computing a sequence of rankings that maximizes consumer-side utility while minimizing producer-side individual unfairness of exposure. While prior work…