Fair Mixup only improves multicalibration fairness for a single large group; vanilla Mixup, especially with multicalibration post-processing, is the most consistent method across many groups.
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Who's the (Multi-)Fairest of Them All: Rethinking Interpolation-Based Data Augmentation Through the Lens of Multicalibration
Fair Mixup only improves multicalibration fairness for a single large group; vanilla Mixup, especially with multicalibration post-processing, is the most consistent method across many groups.