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Fairer non-negative matrix factorization

There has been a recent critical need to study fairness and bias in machine learning (ML) algorithms. Since there is clearly no one-size-fits-all solution to fairness, ML methods should be developed alongside bias mitigation strategies that are practical and approachable to the practitioner. Motivat...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Lara Kassab, Erin George, Deanna Needell, Haowen Geng, Nika Jafar Nia, Aoxi Li
Format: Artigo
Sprache:Inglês
Veröffentlicht: Frontiers Media S.A. 2026-03-01
Schriftenreihe:Frontiers in Big Data
Schlagworte:
dimensionality reduction
Fairer-NMF
fairness
non-negative matrix factorization
topic modeling
Online-Zugang:https://www.frontiersin.org/articles/10.3389/fdata.2026.1737043/full
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