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Faking feature importance: A cautionary tale on the use of
  differentially-private synthetic data

Faking feature importance: A cautionary tale on the use of differentially-private synthetic data

2 March 2022
Oscar Giles
Kasra Hosseini
Grigorios Mingas
Oliver Strickson
Louise A. Bowler
Camila Rangel Smith
H. Wilde
Jen Ning Lim
Bilal A. Mateen
Kasun Amarasinghe
Rayid Ghani
A. Heppenstall
N. Lomax
N. Malleson
Martin O'Reilly
Sebastian Vollmerteke
ArXivPDFHTML

Papers citing "Faking feature importance: A cautionary tale on the use of differentially-private synthetic data"

6 / 6 papers shown
Title
Towards a Theoretical Understanding of Synthetic Data in LLM Post-Training: A Reverse-Bottleneck Perspective
Towards a Theoretical Understanding of Synthetic Data in LLM Post-Training: A Reverse-Bottleneck Perspective
Zeyu Gan
Yong Liu
SyDa
46
1
0
02 Oct 2024
Does Differentially Private Synthetic Data Lead to Synthetic
  Discoveries?
Does Differentially Private Synthetic Data Lead to Synthetic Discoveries?
Ileana Montoya Perez
P. Movahedi
Valtteri Nieminen
A. Airola
T. Pahikkala
29
4
0
20 Mar 2024
Assessment of Differentially Private Synthetic Data for Utility and
  Fairness in End-to-End Machine Learning Pipelines for Tabular Data
Assessment of Differentially Private Synthetic Data for Utility and Fairness in End-to-End Machine Learning Pipelines for Tabular Data
Mayana Pereira
Meghana Kshirsagar
Soumendu Sundar Mukherjee
Rahul Dodhia
J. L. Ferres
Rafael de Sousa
SyDa
45
11
0
30 Oct 2023
SoK: Privacy-Preserving Data Synthesis
SoK: Privacy-Preserving Data Synthesis
Yuzheng Hu
Fan Wu
Yue Liu
Yunhui Long
Gonzalo Munilla Garrido
Chang Ge
Bolin Ding
David A. Forsyth
Bo-wen Li
D. Song
60
26
0
05 Jul 2023
The Berkelmans-Pries Feature Importance Method: A Generic Measure of
  Informativeness of Features
The Berkelmans-Pries Feature Importance Method: A Generic Measure of Informativeness of Features
Joris Pries
Guus Berkelmans
Sandjai Bhulai
R. V. D. Mei
FAtt
17
0
0
11 Jan 2023
On the Utility Recovery Incapability of Neural Net-based Differential
  Private Tabular Training Data Synthesizer under Privacy Deregulation
On the Utility Recovery Incapability of Neural Net-based Differential Private Tabular Training Data Synthesizer under Privacy Deregulation
Yucong Liu
ChiHua Wang
Guang Cheng
29
7
0
28 Nov 2022
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