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--- en:sci22 [2013/09/10 15:02] – tdenoeux
+++ en:sci22 [2014/09/12 11:29] – tdenoeux
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 ====== SCI 22: Modeling and propagation of uncertainties ======
-Instructor: Thierry Denoeux
+**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 (inclusing interval analysis). Numerous examples taken from different domains (Artificial Intelligence, multi-sensor fusion, numerical modeling) will illustrate the theoretical notions.
+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.
-Programme (Automne 2013)
+**Program (Fall 2014)** Room O223 (PG2)
- September: Introduction to uncertainty
+  - 10 September: Introduction to uncertainty
- September: Belief functions: representation of evidence
+  - 17 September: Representation of evidence
-September: Belief functions: combination of evidence
+  - 1 October: Combination of evidence
- October: Refinement and coarsening of a frame of discernment
+  - 4 October: Least commitment principle. Coarsening and refinement
- October:
+  - 8 October: Decision analysis. Classification and clustering
- October: Applications to pattern recognition and information fusion
+  - 15 October:  Applications
- October: Presentation of research papers by students
+  - 18 October: Presentation of research papers by students

UMR CNRS 7253

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