Brendan McMahan: Federated Learning with Formal User-level Differential Privacy Guarantees

Privacy for users is a central goal of cross-device federated learning. This talk begins with a quick overview of federated learning and key privacy principles. We then deep-dive into some recent advances in providing stronger anonymization properties for cross-device federated learning, including the DP-FTRL algorithm that was used to launch a production neural-language model trained with a user-level differential privacy guarantee.