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SCI 22: Modeling and propagation of uncertainties

Instructor: Thierry Denoeux

Description: This course presents the main formalisms for uncertainty representation with emphasis on the theory of belief functions, which generalizes both probability theory and the set-membership approach (including interval analysis). Numerous examples taken from different domains (Artificial Intelligence, multi-sensor fusion, numerical modeling) will illustrate the theoretical notions.

Program (Fall 2014)

Room O223 (PG2)

  1. 10 September: Introduction to uncertainty
  2. 17 September: Representation of evidence
  3. 1 October: Combination of evidence
  4. 4 October: Least commitment principle. Coarsening and refinement
  5. 8 October: Decision analysis. Classification and clustering
  6. 15 October: Applications
  7. 18 October: Presentation of research papers by students

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