13 citations · 13 across the 2 of their papers we have counts for
2 papers
cs.LG2022
Can collaborative learning be private, robust and scalable?
Dmitrii Usynin, Helena Klause, Johannes C. Paetzold +2
In federated learning for medical image analysis, the safety of the learning protocol is paramount. Such settings can often be compromised by adversaries that target either the pri…
cs.LG2022★ 13 cited
Differentially private training of residual networks with scale normalisation
Helena Klause, Alexander Ziller, Daniel Rueckert +2
The training of neural networks with Differentially Private Stochastic Gradient Descent offers formal Differential Privacy guarantees but introduces accuracy trade-offs. In this wo…