Wasserstein-based fairness interpretability framework for machine learning models

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1573-0565

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Wasserstein-based fairness interpretability framework for machine learning models ; volume:111 ; number:9 ; day:21 ; month:7 ; year:2022 ; pages:3307-3357 ; date:9.2022
Machine learning ; 111, Heft 9 (21.7.2022), 3307-3357, 9.2022

Creator: Miroshnikov, Alexey
Kotsiopoulos, Konstandinos
Franks, Ryan
Ravi Kannan, Arjun

Contributor: SpringerLink (Online service)

DOI: 10.1007/s10994-022-06213-9

URN: urn:nbn:de:101:1-2022120221174274815216

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:34 AM CEST

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Miroshnikov, Alexey
Kotsiopoulos, Konstandinos
Franks, Ryan
Ravi Kannan, Arjun
SpringerLink (Online service)

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Wasserstein-based fairness interpretability framework for machine learning models

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