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FairIF: Boosting Fairness in Deep Learning via Influence Functions with
  Validation Set Sensitive Attributes

FairIF: Boosting Fairness in Deep Learning via Influence Functions with Validation Set Sensitive Attributes

15 January 2022
Haonan Wang
Ziwei Wu
Jingrui He
ArXivPDFHTML

Papers citing "FairIF: Boosting Fairness in Deep Learning via Influence Functions with Validation Set Sensitive Attributes"

3 / 3 papers shown
Title
Understanding Programmatic Weak Supervision via Source-aware Influence
  Function
Understanding Programmatic Weak Supervision via Source-aware Influence Function
Jieyu Zhang
Hong Wang
Cheng-Yu Hsieh
Alexander Ratner
TDI
32
9
0
25 May 2022
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
294
4,187
0
23 Aug 2019
Learning Adversarially Fair and Transferable Representations
Learning Adversarially Fair and Transferable Representations
David Madras
Elliot Creager
T. Pitassi
R. Zemel
FaML
213
673
0
17 Feb 2018
1