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cs.LG2023
Computational Asymmetries in Robust Classification
Samuele Marro, Michele Lombardi
In the context of adversarial robustness, we make three strongly related contributions. First, we prove that while attacking ReLU classifiers is -hard, ensuring their…
cs.LG2023
Generalized Disparate Impact for Configurable Fairness Solutions in ML
Luca Giuliani, Eleonora Misino, Michele Lombardi
We make two contributions in the field of AI fairness over continuous protected attributes. First, we show that the Hirschfeld-Gebelein-Renyi (HGR) indicator (the only one currentl…