Federated Learning

An approach to machine learning which addresses problems of data governance and privacy by training algorithms collaboratively without transferring the data to a central location. Each federated device trains on data locally and shares its local model parameters instead of sharing the training data. Different federated learning systems have different topologies that involve different ways of sharing parameters.