92977ae4d2ba21425a59afb269c2a14e-Supplemental.pdf

We revisit survey results from Section 6, and explore the impact of label noise on our proposed method. Each participant was told that an auction would be fair if each ad was presented to each group at equal rates. We train PreferenceNet, perturbing labels according to their distance from the decision boundary. Eliciting preferences from a group is particularly challenging, because these preferences often heterogeneous. Table 2: We simulate preference elicitation of three different definitions of fairness.