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More Data Can Lead Us Astray: Active Data Acquisition in the Presence of
  Label Bias

More Data Can Lead Us Astray: Active Data Acquisition in the Presence of Label Bias

15 July 2022
Yunyi Li
Maria De-Arteaga
M. Saar-Tsechansky
    FaML
ArXivPDFHTML

Papers citing "More Data Can Lead Us Astray: Active Data Acquisition in the Presence of Label Bias"

3 / 3 papers shown
Title
Adaptive Sampling Strategies to Construct Equitable Training Datasets
Adaptive Sampling Strategies to Construct Equitable Training Datasets
William Cai
R. Encarnación
Bobbie Chern
S. Corbett-Davies
Miranda Bogen
Stevie Bergman
Sharad Goel
81
30
0
31 Jan 2022
Improving fairness in machine learning systems: What do industry
  practitioners need?
Improving fairness in machine learning systems: What do industry practitioners need?
Kenneth Holstein
Jennifer Wortman Vaughan
Hal Daumé
Miroslav Dudík
Hanna M. Wallach
FaML
HAI
192
742
0
13 Dec 2018
A statistical framework for fair predictive algorithms
A statistical framework for fair predictive algorithms
K. Lum
J. Johndrow
FaML
174
104
0
25 Oct 2016
1