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Privacy in Practice: Private COVID-19 Detection in X-Ray Images
  (Extended Version)

Privacy in Practice: Private COVID-19 Detection in X-Ray Images (Extended Version)

21 November 2022
Lucas Lange
Maja Schneider
Peter Christen
Erhard Rahm
ArXivPDFHTML

Papers citing "Privacy in Practice: Private COVID-19 Detection in X-Ray Images (Extended Version)"

4 / 4 papers shown
Title
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
FedDPGAN: Federated Differentially Private Generative Adversarial
  Networks Framework for the Detection of COVID-19 Pneumonia
FedDPGAN: Federated Differentially Private Generative Adversarial Networks Framework for the Detection of COVID-19 Pneumonia
Longling Zhang
Bochen Shen
A. Barnawi
Shan Xi
Neeraj Kumar
Yi Wu
FedML
MedIm
79
80
0
26 Apr 2021
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for
  Private Learning
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning
Da Yu
Huishuai Zhang
Wei Chen
Tie-Yan Liu
FedML
SILM
94
110
0
25 Feb 2021
Tempered Sigmoid Activations for Deep Learning with Differential Privacy
Tempered Sigmoid Activations for Deep Learning with Differential Privacy
Nicolas Papernot
Abhradeep Thakurta
Shuang Song
Steve Chien
Ulfar Erlingsson
AAML
147
178
0
28 Jul 2020
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