Introduction to Federated Learning
Federated Learning (FL) is a Machine Learning (ML) paradigm introduced by Google in 2016, in which many clients (e.g., mobile devices or multiple organizations) collaboratively train a model under the orchestration of a central server (e.g., a service provider), while maintaining decentralized training data at all times. It embodies the principles of focused collection, data …