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Bias and unfairness in machine learning models: a systematic literature
  review

Bias and unfairness in machine learning models: a systematic literature review

16 February 2022
T. P. Pagano
R. B. Loureiro
F. V. N. Lisboa
G. O. R. Cruz
R. M. Peixoto
Guilherme A. S. Guimarães
L. L. Santos
Maira M. Araujo
Marco A. S. Cruz
Ewerton L. S. Oliveira
Ingrid Winkler
E. G. S. Nascimento
    FaML
ArXivPDFHTML

Papers citing "Bias and unfairness in machine learning models: a systematic literature review"

2 / 2 papers shown
Title
Integrating Psychometrics and Computing Perspectives on Bias and
  Fairness in Affective Computing: A Case Study of Automated Video Interviews
Integrating Psychometrics and Computing Perspectives on Bias and Fairness in Affective Computing: A Case Study of Automated Video Interviews
Brandon M. Booth
Louis Hickman
Shree Krishna Subburaj
Louis Tay
S. E. Woo
S. D’Mello
FaML
32
18
0
04 May 2023
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
314
4,203
0
23 Aug 2019
1