575 citations · 929 across the 52 of their papers we have counts for
3 papers · 2 filters
Algorithmic stability implies training-conditional coverage for distribution-free prediction methods
Ruiting Liang, Rina Foygel Barber
In a supervised learning problem, given a predicted value that is the output of some trained model, how can we quantify our uncertainty around this prediction? Distribution-free pr…
Distribution-free inference with hierarchical data
Yonghoon Lee, Rina Foygel Barber, Rebecca Willett
This paper studies distribution-free inference in settings where the data set has a hierarchical structure -- for example, groups of observations, or repeated measurements. In such…
De Finetti's theorem and related results for infinite weighted exchangeable sequences
Rina Foygel Barber, Emmanuel J. Candes, Aaditya Ramdas +1
De Finetti's theorem, also called the de Finetti-Hewitt-Savage theorem, is a foundational result in probability and statistics. Roughly, it says that an infinite sequence of exchan…