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A Cautionary Tale: On the Role of Reference Data in Empirical Privacy
  Defenses

A Cautionary Tale: On the Role of Reference Data in Empirical Privacy Defenses

18 October 2023
Caelin Kaplan
Chuan Xu
Othmane Marfoq
Giovanni Neglia
Anderson Santana de Oliveira
    AAML
ArXivPDFHTML

Papers citing "A Cautionary Tale: On the Role of Reference Data in Empirical Privacy Defenses"

4 / 4 papers shown
Title
Hyperparameter Tuning with Renyi Differential Privacy
Hyperparameter Tuning with Renyi Differential Privacy
Nicolas Papernot
Thomas Steinke
125
119
0
07 Oct 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
37
57
0
23 Sep 2021
Stealing Links from Graph Neural Networks
Stealing Links from Graph Neural Networks
Xinlei He
Jinyuan Jia
Michael Backes
Neil Zhenqiang Gong
Yang Zhang
AAML
63
168
0
05 May 2020
Systematic Evaluation of Privacy Risks of Machine Learning Models
Systematic Evaluation of Privacy Risks of Machine Learning Models
Liwei Song
Prateek Mittal
MIACV
189
358
0
24 Mar 2020
1