Combining Stochastic Defenses to Resist Gradient Inversion: An Ablation Study

Fuente: arXiv

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Bibliographic Details
Main Authors:	Scheliga, Daniel, Mäder, Patrick, Seeland, Marco
Format:	Preprint
Published:	2022
Subjects:	Machine Learning Artificial Intelligence Cryptography and Security
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2208.04767