Online conformal prediction with decaying step sizes
Machine Learning
2024-05-29 v2 Machine Learning
Methodology
Abstract
We introduce a method for online conformal prediction with decaying step sizes. Like previous methods, ours possesses a retrospective guarantee of coverage for arbitrary sequences. However, unlike previous methods, we can simultaneously estimate a population quantile when it exists. Our theory and experiments indicate substantially improved practical properties: in particular, when the distribution is stable, the coverage is close to the desired level for every time point, not just on average over the observed sequence.
Cite
@article{arxiv.2402.01139,
title = {Online conformal prediction with decaying step sizes},
author = {Anastasios N. Angelopoulos and Rina Foygel Barber and Stephen Bates},
journal= {arXiv preprint arXiv:2402.01139},
year = {2024}
}