UMR CNRS 7253

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en:sci22 [2014/08/10 13:03] – tdenoeuxen:sci22 [2014/09/12 11:29] – tdenoeux
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 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. 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)**+**Program (Fall 2014)** Room O223 (PG2)
  
   - 10 September: Introduction to uncertainty    - 10 September: Introduction to uncertainty 
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   - 8 October: Decision analysis. Classification and clustering   - 8 October: Decision analysis. Classification and clustering
   - 15 October:  Applications    - 15 October:  Applications 
-  - 22 October: Presentation of research papers by students+  - 18 October: Presentation of research papers by students
  
  

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en/sci22.txt · Last modified: 2014/09/12 11:29 by tdenoeux
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