Tag: near

Near-Optimal Algorithms for Omniprediction arXiv:2501.17205v1 Announce Type: new Abstract: Omnipredictors are simple prediction functions that encode loss-minimizing predictions with respect to a hypothesis class $H$, simultaneously for every loss function within a class of losses $L$. In this work, we give near-optimal learning algorithms for omniprediction, in both the online and offline settings. To begin,…