On the Intrinsic Privacy of Stochastic Gradient Descent

By Stephanie L. Hyland, Shruti Tople. 2019

13 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Natalia Ponomareva
2. Zheng Xu
3. Abhradeep Thakurta
4. Hussein Hazimeh
5. Florian Tramèr
6. H. Brendan McMahan
7. Alexey Kurakin
8. Peter Kairouz

Citations in the corpus

• How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy (2023, background): “While there has been some work that attempts to reason about intrinsic Differential Privacy of some unmodified/standard ML components (e.g., SGD (Hyland & Tople, 2019) and bagging (Liu et al., 2020)), this subfield is still very much nascent and will not be explored in this paper.”