Hosted by the DSI Foundations of Data Science Center; Department of Statistics, Arts and Sciences; and Columbia Engineering
Speaker: Francis Bach, Senior Researcher at INRIA, SIERRA Project-Team Leader, Computer Science Department, École Normale Supérieure
Registration for all CUID holders is preferred. If you do not have an active CUID, registration is required and is due at 12:00 PM the day prior to the seminar. Unfortunately, we cannot guarantee entrance to Columbia’s Morningside campus if you register following 12:00 PM the day prior to the seminar. Thank you for understanding!
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Recent Advances in Uncertainty Quantification: Anytime Guarantees and Multivariate Predictions
Abstract: Quantifying uncertainty in statistics and machine learning is crucial, but challenging in high-dimensional prediction problems. Probabilistic calibration and conformal prediction have emerged as key practical theoretically well-motivated frameworks. In this talk, I will present recent advances that allow greater flexibility in their applications, in terms of anytime guarantees and applications in multivariate prediction problems beyond univariate regression and binary classification.