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Online conformal prediction with decaying step sizes
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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.
Forward citations
Cited by 2 Pith papers
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Relevance-Aware Thresholding in Online Conformal Prediction for Time Series
Replacing the binary inside/outside error in PID and ECI online conformal prediction with smooth relevance functions can shrink prediction intervals while keeping long-run coverage on several time-series benchmarks.
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Dynamic Estimation Loss Control in Variational Quantum Sensing via Online Conformal Inference
A dynamic variational quantum sensing method using online conformal inference controls the long-term estimation loss at a user-specified level while updating circuit and estimator parameters.
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