Online conformal prediction with decaying step sizes
<|reference_start|>Online conformal prediction with decaying step sizes: 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.<|reference_end|>
@article{angelopoulos2024online,
    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},
    archivePrefix={arXiv},
    eprint={2402.01139},
    primaryClass={stat.ML cs.LG stat.ME}
}