Conformalized Online Learning. (arXiv:2205.09095v5 [cs.LG] UPDATED)

Adaptive conformal inference is a highly flexible framework for constructing
uncertainty sets with a valid coverage guarantee in an online setting, in which
the underlying data distribution can drastically -- and even adversarially --
shift over time. In this report, we propose an instantiation of ACI that can be
easily integrated with any online learning algorithm, requiring minimal
implementation effort and computational cost. Additionally, we provide
approaches for constructing intervals that quickly adapt to new changes in the
distribution. Using …

arxiv learning lg online learning