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Online conformal prediction with decaying step sizes

2 February 2024
Anastasios Nikolas Angelopoulos
Rina Foygel Barber
Stephen Bates
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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.

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