If you are trying to register for LISA19, please complete your registration before or after this time period. presented at PEPR'19 2019

by Frank Kargl, Nicolas Papernot,

Summary : This talk will illustrate how learning with rigorous differential privacy guarantees is possible using TensorFlow Privacy, an open-source library that makes it easier not only for developers to train ML models with privacy in real-world systems, but also for researchers to advance the state-of-the-art in ML with strong privacy guarantees.