Multigroup Fairness and Omniprediction: Separations and Equivalences

Excerpt

arXiv:2610.07374v1 Announce Type: new Abstract: Omniprediction is a learning guarantee which requires a single predictor to be competitive relative to the best hypothesis from a benchmark class for any loss chosen from a family of loss functions. Loss Outcome Indistinguishability (loss OI for short) is a stronger notion that implies omniprediction. It requires the predicted distribution on labels to be indistinguishable from the true distribution to tests that depend on the loss functions and th