2.1k citations · 10.8k across the 103 of their papers we have counts for
115 papers
Correcting the Coverage Bias of Quantile Regression
Isaac Gibbs, John J. Cherian, Emmanuel J. Candès
We develop a collection of methods for adjusting the predictions of quantile regression to ensure coverage. Our methods are model agnostic and can be used to correct for high-dimen…
Characterizing the Training-Conditional Coverage of Full Conformal Inference in High Dimensions
Isaac Gibbs, Emmanuel J. Candès
We study the coverage properties of full conformal regression in the proportional asymptotic regime where the ratio of the dimension and the sample size converges to a constant. In…
Posterior Conformal Prediction
Yao Zhang, Emmanuel J. Candès
Conformal prediction is a popular technique for constructing prediction intervals with distribution-free coverage guarantees. The coverage is marginal, meaning it only holds on ave…
RandALO: Out-of-sample risk estimation in no time flat
Parth Nobel, Daniel LeJeune, Emmanuel J. Candès
Estimating out-of-sample risk for models trained on large high-dimensional datasets is an expensive but essential part of the machine learning process, enabling practitioners to op…
Large language model validity via enhanced conformal prediction methods
John J. Cherian, Isaac Gibbs, Emmanuel J. Candès
We develop new conformal inference methods for obtaining validity guarantees on the output of large language models (LLMs). Prior work in conformal language modeling identifies a s…
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…