Rina Foygel Barber

A detailed look at algorithm evaluation and model performance assessment.

Learn how resampling techniques improve the stability of statistical findings.

A new framework for creating reliable and accurate machine learning classifiers.

An exploration of algorithmic stability and testing limitations.

Learn how boosted conformal prediction enhances understanding of uncertainty in models.

Learn how to improve model predictions despite shifting data distributions.