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Autor:
Aditee Kumthekar, Flavien Prost, Li Wei, Xuezhi Wang, Nick Blumm, Pranjal Awasthi, Alex Beutel, Ed H. Chi, Trevor Potter, Jilin Chen
Publikováno v:
AIES
In this work we study the problem of measuring the fairness of a machine learning model under noisy information. Focusing on group fairness metrics, we investigate the particular but common situation when the evaluation requires controlling for the c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a46878b9ca93bcdb663a657aabe3a4ee
http://arxiv.org/abs/2105.09985
http://arxiv.org/abs/2105.09985
