6 papers · 1 filter
Monte Carlo testing: non-asymptotic guarantees without joint exchangeability
Rina Foygel Barber, Aaditya Ramdas
In hypothesis testing, Monte Carlo tests are usually justified either by exact null simulation or by joint exchangeability of the observed data and its simulated copies. This leave…
Conformal prediction after data-dependent model selection
Ruiting Liang, Wanrong Zhu, Rina Foygel Barber
Given a family of pretrained models and a hold-out set, how can we construct a valid conformal prediction set while selecting a model that minimizes the width of the set? If we use…
Approximate co-sufficient sampling with regularization
Wanrong Zhu, Rina Foygel Barber
In this work, we consider the problem of goodness-of-fit (GoF) testing for parametric models. This testing problem involves a composite null hypothesis, due to the unknown values o…
Group-Weighted Conformal Prediction
Aabesh Bhattacharyya, Rina Foygel Barber
Conformal prediction (CP) is a method for constructing a prediction interval around the output of a fitted model, whose validity does not rely on the model being correct--the CP in…
Boosted Conformal Prediction Intervals
Ran Xie, Rina Foygel Barber, Emmanuel J. Candès
This paper introduces a boosted conformal procedure designed to tailor conformalized prediction intervals toward specific desired properties, such as enhanced conditional coverage…
Conformal prediction with local weights: randomization enables local guarantees
Rohan Hore, Rina Foygel Barber
In this work, we consider the problem of building distribution-free prediction intervals with finite-sample conditional coverage guarantees. Conformal prediction (CP) is an increas…