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Creators/Authors contains: "Angelopoulos, Anastasios Nikolas"

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  1. ; ; (, Proceedings of the 41st International Conference on Machine Learning)
    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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    Free, publicly-accessible full text available July 1, 2025
  2. ; ; ; (, Harvard Data Science Review)
    Full Text Available