Private and Fair Machine Learning: Revisiting the Disparate Impact of Differentially Private SGD

Lea Demelius, Dominik Kowald, Simone Kopeinik +2

Differential privacy (DP) is a prominent method for protecting information about individuals during data analysis. Training neural networks with differentially private stochastic g…