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A Possibility in Algorithmic Fairness: Can Calibration and Equal Error
  Rates Be Reconciled?
v1v2v3 (latest)

A Possibility in Algorithmic Fairness: Can Calibration and Equal Error Rates Be Reconciled?

18 February 2020
Claire Lazar Reich
Suhas Vijaykumar
    FaML
ArXiv (abs)PDFHTML

Papers citing "A Possibility in Algorithmic Fairness: Can Calibration and Equal Error Rates Be Reconciled?"

4 / 4 papers shown
Title
Algorithmic Fairness in Performative Policy Learning: Escaping the
  Impossibility of Group Fairness
Algorithmic Fairness in Performative Policy Learning: Escaping the Impossibility of Group Fairness
Seamus Somerstep
Yaácov Ritov
Yuekai Sun
FaML
86
5
0
30 May 2024
Are demographically invariant models and representations in medical
  imaging fair?
Are demographically invariant models and representations in medical imaging fair?
Eike Petersen
Enzo Ferrante
M. Ganz
Aasa Feragen
MedIm
101
10
0
02 May 2023
On (assessing) the fairness of risk score models
On (assessing) the fairness of risk score models
Eike Petersen
M. Ganz
Sune Holm
Aasa Feragen
FaML
67
21
0
17 Feb 2023
Beyond Impossibility: Balancing Sufficiency, Separation and Accuracy
Beyond Impossibility: Balancing Sufficiency, Separation and Accuracy
Limor Gultchin
Vincent Cohen-Addad
Sophie Giffard-Roisin
Varun Kanade
Frederik Mallmann-Trenn
63
4
0
24 May 2022
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