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Adversarial Learned Fair Representations using Dampening and Stacking

Adversarial Learned Fair Representations using Dampening and Stacking

16 March 2022
M. Knobbout
    FaML
ArXiv (abs)PDFHTML

Papers citing "Adversarial Learned Fair Representations using Dampening and Stacking"

5 / 5 papers shown
Title
Adversarial Stacked Auto-Encoders for Fair Representation Learning
Adversarial Stacked Auto-Encoders for Fair Representation Learning
Patrik Kenfack
Adil Khan
Rasheed Hussain
S. M. Ahsan Kazmi
FaML
24
4
0
27 Jul 2021
Using Adversarial Debiasing to Remove Bias from Word Embeddings
Using Adversarial Debiasing to Remove Bias from Word Embeddings
Dana Kenna
FaML
29
4
0
21 Jul 2021
Topic Modelling Meets Deep Neural Networks: A Survey
Topic Modelling Meets Deep Neural Networks: A Survey
He Zhao
Dinh Q. Phung
Viet Huynh
Yuan Jin
Lan Du
Wray Buntine
BDL
36
142
0
28 Feb 2021
Learning Adversarially Fair and Transferable Representations
Learning Adversarially Fair and Transferable Representations
David Madras
Elliot Creager
T. Pitassi
R. Zemel
FaML
382
684
0
17 Feb 2018
Stabilizing Adversarial Nets With Prediction Methods
Stabilizing Adversarial Nets With Prediction Methods
A. Yadav
Sohil Shah
Zheng Xu
David Jacobs
Tom Goldstein
ODL
82
89
0
20 May 2017
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