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stat.ML2026
Tight Sample Complexity for Low-Degree and Sparse Boolean Polynomials
Jasper van Doornmalen, Mathieu Molina, Victor Verdugo +1
Motivated by the optimization of bounded binary black-box functions, we study the problem of learning polynomial surrogates over the Boolean hypercube. To ensure that optimizing th…
stat.ML2022★ 4 cited
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…