Federated Learning and Analytics at Google - Workshop Introduction

Explore federated learning and analytics at Google in this 31-minute TechTalk presented by Sean Augenstein and Brendan McMahan. Dive into the concept of decentralized and privacy-preserving machine learning, pioneered by McMahan's team. Learn about the four privacy principles, cross-device federated learning, data minimization techniques, and the tradeoffs involved. Discover practical applications like Gboard privacy and neural network training. Gain insights into Tensorflow Federated, federated analytics, and cutting-edge research topics such as federated dropout and embedding selection. Engage with the speakers' expertise in online learning, large-scale convex optimization, and reinforcement learning as they address questions and discuss the future of privacy-preserving machine learning techniques.