4 papers
Conformal online model aggregation
Matteo Gasparin, Aaditya Ramdas
Conformal prediction equips machine learning models with a reasonable notion of uncertainty quantification without making strong distributional assumptions. It wraps around any pre…
Improving the statistical efficiency of cross-conformal prediction
Matteo Gasparin, Aaditya Ramdas
Vovk (2015) introduced cross-conformal prediction, a modification of split conformal designed to improve the width of prediction sets. The method, when trained with a miscoverage r…
Combining exchangeable p-values
Matteo Gasparin, Ruodu Wang, Aaditya Ramdas
The problem of combining p-values is an old and fundamental one, and the classic assumption of independence is often violated or unverifiable in many applications. There are many w…
Merging uncertainty sets via majority vote
Matteo Gasparin, Aaditya Ramdas
Given uncertainty sets that are arbitrarily dependent -- for example, confidence intervals for an unknown parameter obtained with different estimators, or prediction sets o…