311 citations · 601 across the 23 of their papers we have counts for
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stat.ML2020★ 26 cited
Tempered Sigmoid Activations for Deep Learning with Differential Privacy
Nicolas Papernot, Abhradeep Thakurta, Shuang Song +2
Because learning sometimes involves sensitive data, machine learning algorithms have been extended to offer privacy for training data. In practice, this has been mostly an aftertho…
stat.ML2018★ 311 cited
Scalable Private Learning with PATE
Nicolas Papernot, Shuang Song, Ilya Mironov +3
The rapid adoption of machine learning has increased concerns about the privacy implications of machine learning models trained on sensitive data, such as medical records or other…