11 citations · 22 across the 5 of their papers we have counts for
5 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…
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…
Statistical Inference for Fairness Auditing
John J. Cherian, Emmanuel J. Candès
Before deploying a black-box model in high-stakes problems, it is important to evaluate the model's performance on sensitive subpopulations. For example, in a recidivism prediction…
Conformal Prediction With Conditional Guarantees
Isaac Gibbs, John J. Cherian, Emmanuel J. Candès
We consider the problem of constructing distribution-free prediction sets with finite-sample conditional guarantees. Prior work has shown that it is impossible to provide exact con…
Efficient hyperparameter optimization by way of PAC-Bayes bound minimization
John J. Cherian, Andrew G. Taube, Robert T. McGibbon +6
Identifying optimal values for a high-dimensional set of hyperparameters is a problem that has received growing attention given its importance to large-scale machine learning appli…