3 papers
stat.ME2025
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…
math.ST2025
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…
math.PR2018
Asymptotic Properties of Random Voronoi Cells with Arbitrary Underlying Density
Isaac Gibbs, Linan Chen
We consider the Voronoi diagram generated by i.i.d. -valued random variables with an arbitrary underlying probability density function on ,…