Federated Learning: According to the first edition of the EU-U.S. terminology and taxonomy for artificial intelligence, the term “Federated Learning” means:
Federated learning is a machine learning model which addresses the problem of data governance and privacy by training algorithms collaboratively without transferring the data to another location. Each federated device shares its local model parameters instead of sharing the whole dataset used to train it and the federated learning topology defines the way parameters are shared.
