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Bayesian Modeling of Intersectional Fairness: The Variance of Bias

Bayesian Modeling of Intersectional Fairness: The Variance of Bias

18 November 2018
James R. Foulds
Rashidul Islam
Kamrun Naher Keya
Shimei Pan
ArXivPDFHTML

Papers citing "Bayesian Modeling of Intersectional Fairness: The Variance of Bias"

12 / 12 papers shown
Title
A structured regression approach for evaluating model performance across
  intersectional subgroups
A structured regression approach for evaluating model performance across intersectional subgroups
Christine Herlihy
Kimberly Truong
Alexandra Chouldechova
Miroslav Dudik
49
4
0
26 Jan 2024
Intersectional Fairness: A Fractal Approach
Intersectional Fairness: A Fractal Approach
Giulio Filippi
Sara Zannone
Adriano Soares Koshiyama
27
1
0
24 Feb 2023
Multi-dimensional discrimination in Law and Machine Learning -- A
  comparative overview
Multi-dimensional discrimination in Law and Machine Learning -- A comparative overview
Arjun Roy
J. Horstmann
Eirini Ntoutsi
FaML
21
20
0
12 Feb 2023
Uncertainty in Fairness Assessment: Maintaining Stable Conclusions
  Despite Fluctuations
Uncertainty in Fairness Assessment: Maintaining Stable Conclusions Despite Fluctuations
Ainhize Barrainkua
Paula Gordaliza
Jose A. Lozano
Novi Quadrianto
26
1
0
02 Feb 2023
A Survey on Preserving Fairness Guarantees in Changing Environments
A Survey on Preserving Fairness Guarantees in Changing Environments
Ainhize Barrainkua
Paula Gordaliza
Jose A. Lozano
Novi Quadrianto
FaML
31
3
0
14 Nov 2022
Fair Inference for Discrete Latent Variable Models
Fair Inference for Discrete Latent Variable Models
Rashidul Islam
Shimei Pan
James R. Foulds
FaML
50
1
0
15 Sep 2022
Bounding and Approximating Intersectional Fairness through Marginal
  Fairness
Bounding and Approximating Intersectional Fairness through Marginal Fairness
M. Molina
P. Loiseau
34
8
0
12 Jun 2022
Towards Intersectionality in Machine Learning: Including More
  Identities, Handling Underrepresentation, and Performing Evaluation
Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation
Angelina Wang
V. V. Ramaswamy
Olga Russakovsky
FaML
34
92
0
10 May 2022
FARF: A Fair and Adaptive Random Forests Classifier
FARF: A Fair and Adaptive Random Forests Classifier
Wenbin Zhang
Albert Bifet
Xiangliang Zhang
Jeremy C. Weiss
Wolfgang Nejdl
FaML
21
52
0
17 Aug 2021
Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data
  and Bayesian Inference
Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference
Disi Ji
Padhraic Smyth
M. Steyvers
39
45
0
19 Oct 2020
Fair Bayesian Optimization
Fair Bayesian Optimization
Valerio Perrone
Michele Donini
Muhammad Bilal Zafar
Robin Schmucker
K. Kenthapadi
Cédric Archambeau
FaML
27
84
0
09 Jun 2020
Learning Fair Representations for Kernel Models
Learning Fair Representations for Kernel Models
Zilong Tan
Samuel Yeom
Matt Fredrikson
Ameet Talwalkar
FaML
35
25
0
27 Jun 2019
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