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FA(IR)2MA-GLVQ – A hidden-feature-bias mitigation approach for fairness in classification learning based on generalized matrix learning vector quantization.

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Bibliographic Details
Title: FA(IR)2MA-GLVQ – A hidden-feature-bias mitigation approach for fairness in classification learning based on generalized matrix learning vector quantization.
Authors: Kaden, Marika1, kaden1@hs-mittweida.de, Schubert, Ronny1, Voigt, Julius1, Reuss, Lynn1, Engelsberger, Alexander1, Lövdal, Sofie2,3, van den Brandhof, Elina L.2,4, Biehl, Michael2,5, Villmann, Thomas1,6, villmann@hs-mittweida.de
Source: Neurocomputing; May2026, Vol. 678, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
Description
ISSN:09252312
DOI:10.1016/j.neucom.2026.133200