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Casual Conversations v2: Designing a large consent-driven dataset to
  measure algorithmic bias and robustness

Casual Conversations v2: Designing a large consent-driven dataset to measure algorithmic bias and robustness

10 November 2022
C. Hazirbas
Yejin Bang
Tiezheng Yu
Parisa Assar
Bilal Porgali
Vítor Albiero
Stefan Hermanek
Jacqueline Pan
Emily McReynolds
Miranda Bogen
Pascale Fung
Cristian Canton Ferrer
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Papers citing "Casual Conversations v2: Designing a large consent-driven dataset to measure algorithmic bias and robustness"

3 / 3 papers shown
Title
Learning Fair Classifiers with Partially Annotated Group Labels
Learning Fair Classifiers with Partially Annotated Group Labels
Sangwon Jung
Sanghyuk Chun
Taesup Moon
63
46
0
29 Nov 2021
A Survey on Bias in Visual Datasets
A Survey on Bias in Visual Datasets
Simone Fabbrizzi
Symeon Papadopoulos
Eirini Ntoutsi
Y. Kompatsiaris
121
121
0
16 Jul 2021
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
305
4,203
0
23 Aug 2019
1