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Instructor: Thierry Denoeux
The theory of epistemic random fuzzy sets has been recently proposed as a very general formalism for uncertain reasoning, encompassing both the Dempster-Shafer theory of evidence and possibility theory as special cases. This tutorial is intended to provide an introduction to this new framework and to demonstrate its application to uncertainty quantification in machine learning.
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