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On the relation between accuracy and fairness in binary classification

On the relation between accuracy and fairness in binary classification

21 May 2015
Indrė Žliobaitė
    FaML
ArXivPDFHTML

Papers citing "On the relation between accuracy and fairness in binary classification"

3 / 3 papers shown
Title
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models
Ruta Binkyte
Ivaxi Sheth
Zhijing Jin
Mohammad Havaei
Bernhard Schölkopf
Mario Fritz
369
1
0
28 Feb 2025
Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization
Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization
Simone Bombari
Marco Mondelli
172
0
0
03 Feb 2025
A Review of Fairness and A Practical Guide to Selecting Context-Appropriate Fairness Metrics in Machine Learning
A Review of Fairness and A Practical Guide to Selecting Context-Appropriate Fairness Metrics in Machine Learning
Caleb J. S. Barr
Olivia Erdelyi
Paul D. Docherty
Randolph C. Grace
FaML
129
0
0
10 Nov 2024
1