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pro vyhledávání: '"Remerscheid, Nicolas"'
The arguably most widely employed algorithm to train deep neural networks with Differential Privacy is DPSGD, which requires clipping and noising of per-sample gradients. This introduces a reduction in model utility compared to non-private training.
Externí odkaz:
http://arxiv.org/abs/2205.04095
Autor:
Ziller, Alexander, Usynin, Dmitrii, Remerscheid, Nicolas, Knolle, Moritz, Makowski, Marcus, Braren, Rickmer, Rueckert, Daniel, Kaissis, Georgios
Collaborative machine learning techniques such as federated learning (FL) enable the training of models on effectively larger datasets without data transfer. Recent initiatives have demonstrated that segmentation models trained with FL can achieve pe
Externí odkaz:
http://arxiv.org/abs/2107.02586