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cs.LG2025
Improving Coverage in Combined Prediction Sets with Weighted p-values
Gina Wong, Drew Prinster, Suchi Saria +2
Conformal prediction quantifies the uncertainty of machine learning models by augmenting point predictions with valid prediction sets. For complex scenarios involving multiple tria…
cs.LG2025★ 1 cited
WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales
Drew Prinster, Xing Han, Anqi Liu +1
Responsibly deploying artificial intelligence (AI) / machine learning (ML) systems in high-stakes settings arguably requires not only proof of system reliability, but also continua…
cs.LG2024
Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them)
Drew Prinster, Samuel Stanton, Anqi Liu +1
As artificial intelligence (AI) / machine learning (ML) gain widespread adoption, practitioners are increasingly seeking means to quantify and control the risk these systems incur.…