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SoK: Privacy-Preserving Data Synthesis

SoK: Privacy-Preserving Data Synthesis

5 July 2023
Yuzheng Hu
Fan Wu
Q. Li
Yunhui Long
Gonzalo Munilla Garrido
Chang Ge
Bolin Ding
David A. Forsyth
Bo-wen Li
D. Song
ArXivPDFHTML

Papers citing "SoK: Privacy-Preserving Data Synthesis"

10 / 10 papers shown
Title
The DCR Delusion: Measuring the Privacy Risk of Synthetic Data
The DCR Delusion: Measuring the Privacy Risk of Synthetic Data
Zexi Yao
Natasa Krco
Georgi Ganev
Yves-Alexandre de Montjoye
55
0
0
02 May 2025
The Importance of Being Discrete: Measuring the Impact of Discretization in End-to-End Differentially Private Synthetic Data
The Importance of Being Discrete: Measuring the Impact of Discretization in End-to-End Differentially Private Synthetic Data
Georgi Ganev
Meenatchi Sundaram Muthu Selva Annamalai
Sofiane Mahiou
Emiliano De Cristofaro
24
2
0
09 Apr 2025
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
Chen Gong
Kecen Li
Zinan Lin
Tianhao Wang
47
3
0
18 Mar 2025
Privacy Vulnerabilities in Marginals-based Synthetic Data
Privacy Vulnerabilities in Marginals-based Synthetic Data
Steven Golob
Sikha Pentyala
Anuar Maratkhan
Martine De Cock
19
3
0
07 Oct 2024
Synthetic Data: Revisiting the Privacy-Utility Trade-off
Synthetic Data: Revisiting the Privacy-Utility Trade-off
Fatima Jahan Sarmin
Atiquer Rahman Sarkar
Yang Wang
Noman Mohammed
25
3
0
09 Jul 2024
Differentially Private Synthetic Data via Foundation Model APIs 1:
  Images
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zi-Han Lin
Sivakanth Gopi
Janardhan Kulkarni
Harsha Nori
Sergey Yekhanin
22
36
0
24 May 2023
Diffusion Models: A Comprehensive Survey of Methods and Applications
Diffusion Models: A Comprehensive Survey of Methods and Applications
Ling Yang
Zhilong Zhang
Yingxia Shao
Shenda Hong
Runsheng Xu
Yue Zhao
Wentao Zhang
Bin Cui
Ming-Hsuan Yang
DiffM
MedIm
221
1,277
0
02 Sep 2022
Improving Privacy-Preserving Vertical Federated Learning by Efficient
  Communication with ADMM
Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM
Chulin Xie
Pin-Yu Chen
Qinbin Li
Arash Nourian
Ce Zhang
Bo Li
FedML
23
16
0
20 Jul 2022
Realistic galaxy image simulation via score-based generative models
Realistic galaxy image simulation via score-based generative models
Michael J. Smith
James E. Geach
Ryan A. Jackson
Nikhil Arora
C. Stone
Stéphane Courteau
DiffM
29
31
0
02 Nov 2021
Robin Hood and Matthew Effects: Differential Privacy Has Disparate
  Impact on Synthetic Data
Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data
Georgi Ganev
Bristena Oprisanu
Emiliano De Cristofaro
32
57
0
23 Sep 2021
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