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Interpretability for human-friendly machine learning models

Résumé rédigé par
Directeur de thèse:
Doctorant: Thibault LAUGEL
Unité de recherche UMR 7606 Laboratoire d'informatique de Paris 6

Projet

The main goal of this thesis is to study interpretability and both to propose new frameworks to formally define human-friendly decisions and to apply them to the paradigm of supervised machine learning models and more precisely classification.