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On the Privacy Properties of GAN-generated Samples

On the Privacy Properties of GAN-generated Samples

Zinan Lin
Vyas Sekar
Giulia Fanti
    PICV
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Papers citing "On the Privacy Properties of GAN-generated Samples"

16 / 16 papers shown
Title
Private Federated Learning using Preference-Optimized Synthetic Data
Private Federated Learning using Preference-Optimized Synthetic Data
Charlie Hou
Mei-Yu Wang
Yige Zhu
Daniel Lazar
Giulia Fanti
FedML
Presented at ResearchTrend Connect | FedML on
183
2
0
23 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
215
5
0
18 Mar 2025
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs
Charlie Hou
Akshat Shrivastava
Hongyuan Zhan
Rylan Conway
Trang Le
Adithya Sagar
Giulia Fanti
Daniel Lazar
118
15
0
05 Jun 2024
Generative Semi-supervised Learning with Meta-Optimized Synthetic Samples
Generative Semi-supervised Learning with Meta-Optimized Synthetic Samples
Shinýa Yamaguchi
101
2
0
28 Sep 2023
Ten Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-art
Ten Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-art
Tanujit Chakraborty
Ujjwal Reddy K S
Shraddha M. Naik
Madhurima Panja
B. Manvitha
112
74
0
30 Aug 2023
Adversarial Robustness in Unsupervised Machine Learning: A Systematic Review
Adversarial Robustness in Unsupervised Machine Learning: A Systematic Review
Mathias Lundteigen Mohus
Jinyue Li
AAML
87
1
0
01 Jun 2023
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin
Sivakanth Gopi
Janardhan Kulkarni
Harsha Nori
Sergey Yekhanin
175
44
0
24 May 2023
On Rényi Differential Privacy in Statistics-Based Synthetic Data Generation
On Rényi Differential Privacy in Statistics-Based Synthetic Data Generation
Takayuki Miura
Toshiki Shibahara
M. Kii
Atsunori Ichikawa
Juko Yamamoto
Koji Chida
SyDa
54
0
0
31 Mar 2023
On the causality-preservation capabilities of generative modelling
On the causality-preservation capabilities of generative modelling
Yves-Cédric Bauwelinckx
Jan Dhaene
Tim Verdonck
Milan van den Heuvel
CMLAI4CE
98
1
0
03 Jan 2023
Differentially Private Learning of Hawkes Processes
Differentially Private Learning of Hawkes Processes
Mohsen Ghassemi
Eleonora Kreavcić
Niccolò Dalmasso
Vamsi K. Potluru
T. Balch
Manuela Veloso
116
1
0
27 Jul 2022
RelaxLoss: Defending Membership Inference Attacks without Losing Utility
RelaxLoss: Defending Membership Inference Attacks without Losing Utility
Dingfan Chen
Ning Yu
Mario Fritz
123
43
0
12 Jul 2022
ChildPredictor: A Child Face Prediction Framework with Disentangled Learning
ChildPredictor: A Child Face Prediction Framework with Disentangled Learning
Yuzhi Zhao
L. Po
Xuehui Wang
Qiong Yan
Wei Shen
...
C. Wong
Chiu-Sing Pang
Weifeng Ou
Weikang Yu
Buhua Liu
CVBM
120
8
0
21 Apr 2022
Stability and Generalization of Differentially Private Minimax Problems
Stability and Generalization of Differentially Private Minimax Problems
Yilin Kang
Yong Liu
Jian Li
Weiping Wang
136
3
0
11 Apr 2022
Training face verification models from generated face identity data
Training face verification models from generated face identity data
Dennis Conway
Loïc Simon
Alexis Lechervy
F. Jurie
CVBM
51
0
0
02 Aug 2021
TableGAN-MCA: Evaluating Membership Collisions of GAN-Synthesized Tabular Data Releasing
TableGAN-MCA: Evaluating Membership Collisions of GAN-Synthesized Tabular Data Releasing
Aoting Hu
Renjie Xie
Zhigang Lu
A. Hu
Minhui Xue
MIACV
121
15
0
28 Jul 2021
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
Xinjian Luo
Xiangqi Zhu
FedML
190
27
0
27 Apr 2020