Improved Bounds for Swap Multicalibration and Swap Omniprediction
–Neural Information Processing Systems
In this paper, we consider the related problems of multicalibration -- a multigroup fairness notion and omniprediction -- a simultaneous loss minimization paradigm, both in the distributional and online settings. The recent work of Garg et al. (2024) raised the open problem of whether it is possible to efficiently achieve O( T) ℓ2-multicalibration error against bounded linear functions. In this paper, we answer this question in a strongly affirmative sense.
Neural Information Processing Systems
Jun-15-2026, 11:30:20 GMT