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Exploiting Fairness to Enhance Sensitive Attributes Reconstruction
2 September 2022
Julien Ferry
Ulrich Aïvodji
Sébastien Gambs
Marie-José Huguet
Mohamed Siala
AAML
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Papers citing
"Exploiting Fairness to Enhance Sensitive Attributes Reconstruction"
12 / 12 papers shown
Title
Training Set Reconstruction from Differentially Private Forests: How Effective is DP?
Alice Gorgé
Julien Ferry
Sébastien Gambs
Thibaut Vidal
67
0
0
07 Feb 2025
Trained Random Forests Completely Reveal your Dataset
Julien Ferry
Ricardo Fukasawa
Timothée Pascal
Thibaut Vidal
AAML
29
6
0
29 Feb 2024
SoK: Taming the Triangle -- On the Interplays between Fairness, Interpretability and Privacy in Machine Learning
Julien Ferry
Ulrich Aïvodji
Sébastien Gambs
Marie-José Huguet
Mohamed Siala
FaML
26
5
0
22 Dec 2023
SoK: Unintended Interactions among Machine Learning Defenses and Risks
Vasisht Duddu
S. Szyller
Nadarajah Asokan
AAML
47
2
0
07 Dec 2023
Survey on AI Ethics: A Socio-technical Perspective
Dave Mbiazi
Meghana Bhange
Maryam Babaei
Ivaxi Sheth
Patrik Kenfack
23
4
0
28 Nov 2023
Bias Testing and Mitigation in LLM-based Code Generation
Dong Huang
Qingwen Bu
Jie M. Zhang
Xiaofei Xie
Junjie Chen
Heming Cui
45
20
0
03 Sep 2023
Probabilistic Dataset Reconstruction from Interpretable Models
Julien Ferry
Ulrich Aïvodji
Sébastien Gambs
Marie-José Huguet
Mohamed Siala
24
5
0
29 Aug 2023
Fairness Under Demographic Scarce Regime
Patrik Kenfack
Samira Ebrahimi Kahou
Ulrich Aïvodji
41
3
0
24 Jul 2023
Adversarial attacks and defenses in explainable artificial intelligence: A survey
Hubert Baniecki
P. Biecek
AAML
42
63
0
06 Jun 2023
On the Alignment of Group Fairness with Attribute Privacy
Jan Aalmoes
Vasisht Duddu
A. Boutet
38
2
0
18 Nov 2022
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
323
4,212
0
23 Aug 2019
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
207
2,084
0
24 Oct 2016
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