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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization · Study

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ArticleTackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization

Laurent Risser2022

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Articlegreen2022

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization

Laurent Risser · Alberto González-Sanz · Quentin Vincenot · Jean–Michel Loubes

15 citations·0/0 files stored·Journal of Mathematical Imaging and Vision

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Ethics and Social Impacts of AI Explainable Artificial Intelligence (XAI)Imbalanced Data Classification Techniques

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References

2018Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification 2016Equality of Opportunity in Supervised Learning 2017Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments 2015Certifying and Removing Disparate Impact 2017Counterfactual Fairness 2012Fairness-Aware Classifier with Prejudice Remover Regularizer 2017Fairness Beyond Disparate Treatment & Disparate Impact 2016Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment

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Year2022

Typearticle

Published2022-04-27

VenueJournal of Mathematical Imaging and Vision

ISSN-L0924-9907

Languageen

Citations15

Files0 public / 0

ShelfEthics and Social Impacts of AI

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doi10.1007/s10851-022-01090-2

openalex_workW3086694263

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