Data Preprocessing to Mitigate Bias with Boosted Fair Mollifiers

Alexander Soen
Alexander Soen
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Abstract:

In a recent paper, Celis et al. (2020) introduced a new approach to fairness that corrects the data distribution itself. The approach is computationally appealing, but its approximation guarantees with respect to the target distribution can be quite loose as they need to rely on a (typically limited) number of constraints on data-based ...More

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