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UID:1191@cran.univ-lorraine.fr
DTSTART;TZID=Europe/Paris:20260127T103000
DTEND;TZID=Europe/Paris:20260127T113000
DTSTAMP:20260305T133131Z
URL:https://www.cran.univ-lorraine.fr/events/5374/
SUMMARY:Séminaire de Leonardo Tomazeli Duarte (Unicamp\, Brésil)
DESCRIPTION:Speaker: Leonardo Tomazeli Duarte\, University of Campinas (Uni
 camp\, Brazil)\nTitle: Fairness-Aware Unsupervised Learning: Contributions
  to PCA and Data Aggregation\nLocation: SiMul meeting room\, Faculté des 
 Sciences et Technologies\, Henri Poincaré Building\, 4th floor\nAbstract:
 \nIn this talk\, we address fairness issues in unsupervised learning and d
 ata aggregation. First\, we show that classical principal component analys
 is (PCA) may induce disparities in reconstruction errors across sensitive 
 groups\, leading to biased representations. A simple fairness-aware PCA ap
 proach is presented\, based on a one-dimensional search that exploits the 
 closed-form solution of PCA\, significantly reducing group disparities wit
 h minimal loss in overall performance. Second\, we discuss fairness in mul
 ticriteria decision analysis\, introducing a framework for adjusting aggre
 gation operators to produce fairer rankings. The approach relies on optimi
 zing a fairness metric for both additive weighting and Choquet integral mo
 dels\, and its effectiveness is demonstrated on synthetic and real dataset
 s.
CATEGORIES:Séminaires projet SiMul
LOCATION:CRAN - FST - 4ème\, Campus Sciences\, Boulevard des Aiguillettes\
 , Vandoeuvre-lès-Nancy\, 54506\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Campus Sciences\, Boulevard
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 100;X-TITLE=CRAN - FST - 4ème:geo:0,0
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