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De-biasing "bias" measurement

De-biasing "bias" measurement

11 May 2022
K. Lum
Yunfeng Zhang
Amanda Bower
ArXivPDFHTML

Papers citing "De-biasing "bias" measurement"

16 / 16 papers shown
Title
A Tutorial On Intersectionality in Fair Rankings
Chiara Criscuolo
Davide Martinenghi
Giuseppe Piccirillo
FaML
72
0
0
07 Feb 2025
The Intersectionality Problem for Algorithmic Fairness
The Intersectionality Problem for Algorithmic Fairness
Johannes Himmelreich
Arbie Hsu
Kristian Lum
Ellen Veomett
FaML
39
0
0
04 Nov 2024
(Un)certainty of (Un)fairness: Preference-Based Selection of Certainly
  Fair Decision-Makers
(Un)certainty of (Un)fairness: Preference-Based Selection of Certainly Fair Decision-Makers
Manh Khoi Duong
Stefan Conrad
UD
FaML
50
0
0
19 Sep 2024
Measuring and Mitigating Bias for Tabular Datasets with Multiple
  Protected Attributes
Measuring and Mitigating Bias for Tabular Datasets with Multiple Protected Attributes
Manh Khoi Duong
Stefan Conrad
24
1
0
29 May 2024
Fairness Hacking: The Malicious Practice of Shrouding Unfairness in
  Algorithms
Fairness Hacking: The Malicious Practice of Shrouding Unfairness in Algorithms
Kristof Meding
Thilo Hagendorff
41
7
0
12 Nov 2023
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda
  for Developing Practical Guidelines and Tools
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools
Maximilian Schambach
Rakshit Naidu
Rayid Ghani
Kit T. Rodolfa
Daniel E. Ho
Hoda Heidari
FaML
35
14
0
29 Sep 2023
LUCID-GAN: Conditional Generative Models to Locate Unfairness
LUCID-GAN: Conditional Generative Models to Locate Unfairness
Andres Algaba
Carmen Mazijn
Carina E. A. Prunkl
J. Danckaert
Vincent Ginis
SyDa
39
1
0
28 Jul 2023
Are fairness metric scores enough to assess discrimination biases in
  machine learning?
Are fairness metric scores enough to assess discrimination biases in machine learning?
Fanny Jourdan
Laurent Risser
Jean-Michel Loubes
Nicholas M. Asher
FaML
16
5
0
08 Jun 2023
Data Bias Management
Data Bias Management
Gianluca Demartini
Kevin Roitero
Stefano Mizzaro
26
5
0
15 May 2023
Can Fairness be Automated? Guidelines and Opportunities for
  Fairness-aware AutoML
Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML
Hilde J. P. Weerts
Florian Pfisterer
Matthias Feurer
Katharina Eggensperger
Eddie Bergman
Noor H. Awad
Joaquin Vanschoren
Mykola Pechenizkiy
B. Bischl
Frank Hutter
FaML
41
18
0
15 Mar 2023
Fair Enough: Standardizing Evaluation and Model Selection for Fairness
  Research in NLP
Fair Enough: Standardizing Evaluation and Model Selection for Fairness Research in NLP
Xudong Han
Timothy Baldwin
Trevor Cohn
34
12
0
11 Feb 2023
Fairness and Sequential Decision Making: Limits, Lessons, and
  Opportunities
Fairness and Sequential Decision Making: Limits, Lessons, and Opportunities
Samer B. Nashed
Justin Svegliato
Su Lin Blodgett
FaML
32
6
0
13 Jan 2023
A Keyword Based Approach to Understanding the Overpenalization of
  Marginalized Groups by English Marginal Abuse Models on Twitter
A Keyword Based Approach to Understanding the Overpenalization of Marginalized Groups by English Marginal Abuse Models on Twitter
Kyra Yee
Alice Schoenauer Sebag
Olivia Redfield
Emily Sheng
Matthias Eck
Luca Belli
28
2
0
07 Oct 2022
To the Fairness Frontier and Beyond: Identifying, Quantifying, and
  Optimizing the Fairness-Accuracy Pareto Frontier
To the Fairness Frontier and Beyond: Identifying, Quantifying, and Optimizing the Fairness-Accuracy Pareto Frontier
Camille Olivia Little
Michael Weylandt
Genevera I. Allen
27
13
0
31 May 2022
Characterizing Intersectional Group Fairness with Worst-Case Comparisons
Characterizing Intersectional Group Fairness with Worst-Case Comparisons
A. Ghosh
Lea Genuit
Mary Reagan
FaML
94
51
0
05 Jan 2021
Learning Adversarially Fair and Transferable Representations
Learning Adversarially Fair and Transferable Representations
David Madras
Elliot Creager
T. Pitassi
R. Zemel
FaML
233
674
0
17 Feb 2018
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