Is the Volume of a Credal Set a Good Measure for Epistemic Uncertainty - UAI 2023 Oral Session 2

Explore a thought-provoking conference talk from the Uncertainty in Artificial Intelligence (UAI) 2023 Oral Session that delves into the question: "Is the Volume of a Credal Set a Good Measure for Epistemic Uncertainty?" Presented by Yusuf Sale, Michele Caprio, and Eyke Hüllermeier, this 25-minute presentation examines the use of credal sets as an alternative to single probability measures for representing uncertainty in machine learning and artificial intelligence. Discover how the geometric representation of credal sets as d-dimensional polytopes provides insights into epistemic uncertainty. Learn about the researchers' findings, which suggest that while the volume of a credal set's geometric representation is a meaningful measure of epistemic uncertainty in binary classification, it may be less effective for multi-class classification. Gain valuable insights into the importance of carefully specifying and employing uncertainty measures in machine learning, and become aware of potential pitfalls in this critical area of study.