Quantifying identifiability to choose and audit $\epsilon$ in differentially private deep learning

Daniel Bernau, Günther Eibl, Philip W. Grassal +2

Differential privacy allows bounding the influence that training data records have on a machine learning model. To use differential privacy in machine learning, data scientists mus…