Explicit Asymptotic Bounds for Sequential Calibration Beyond $T^{2/3}$

Excerpt

arXiv:2610.07623v1 Announce Type: cross Abstract: Probability forecasts are calibrated when predicted probabilities match empirical outcome frequencies: among events assigned a probability $p$, we'd hope that the fraction of positive outcomes is close to $p$. We study the problem of sequential forecasting of binary outcomes. The classical $O(T^{2/3})$ bound on expected cumulative $\ell_1$-calibration error established by Foster and Vohra stood for over two decades until Dagan et al. reduced the