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A Novel Approach for Fair Principal Component Analysis Based on Eigendecomposition
16 references·0 citing·37 second hop
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References

  • 2012Fairness through awareness3,545 cited
  • 2016Equality of Opportunity in Supervised Learning2,733 cited
  • 2016Inherent Trade-Offs in the Fair Determination of Risk Scores1,433 cited
  • 2018Fairness definitions explained1,133 cited
  • 2018The accuracy, fairness, and limits of predicting recidivism1,123 cited
  • 2008The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients881 cited
  • 2020Fairness in Machine Learning299 cited
  • 2021Machine learning and algorithmic fairness in public and population health219 cited
  • 2020Empirical observation of negligible fairness-accuracy trade-offs in machine learning for public policy97 cited
  • 2018The Price of Fair PCA: One Extra Dimension84 cited
  • 2020Fairness in Semi-Supervised Learning: Unlabeled Data Help to Reduce Discrimination54 cited
  • 2019The price of fairness - A framework to explore trade-offs in algorithmic fairness38 cited
  • 2021Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination38 cited
  • 2019Convex Formulations for Fair Principal Component Analysis37 cited
  • 2022Efficient fair principal component analysis

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36 cited
  • 2021Integrating Psychometrics and Computing Perspectives on Bias and Fairness in Affective Computing: A case study of automated video interviews23 cited
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