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DiPSeN: Differentially Private Self-normalizing Neural Networks For
  Adversarial Robustness in Federated Learning

DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning

Computers & security (Comput. Secur.), 2021
8 January 2021
Olakunle Ibitoye
M. O. Shafiq
Ashraf Matrawy
    FedML
ArXiv (abs)PDFHTML

Papers citing "DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning"

3 / 3 papers shown
SA-ADP: Sensitivity-Aware Adaptive Differential Privacy for Large Language Models
SA-ADP: Sensitivity-Aware Adaptive Differential Privacy for Large Language Models
Stella Etuk
Ashraf Matrawy
172
0
0
01 Dec 2025
On the Security & Privacy in Federated Learning
On the Security & Privacy in Federated Learning
Gorka Abad
S. Picek
Víctor Julio Ramírez-Durán
A. Urbieta
378
13
0
10 Dec 2021
Gradient Masking and the Underestimated Robustness Threats of
  Differential Privacy in Deep Learning
Gradient Masking and the Underestimated Robustness Threats of Differential Privacy in Deep Learning
Franziska Boenisch
Philip Sperl
Konstantin Böttinger
AAML
189
19
0
17 May 2021
1
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