Federated Learning: A signal processing perspective

The dramatic success of deep learning is largely due to the availability data. Data samples are often acquired on edge devices, such as smartphones, vehicles, and sensors, in some cases cannot be shared privacy considerations. Federated an emerging machine paradigm for training models across multiple devices holding local data sets, without explicitly exchanging Learning a federated manner differs from conventional centralized poses several core unique challenges requirements, which closely related classical problems studied areas signal processing communications. Consequently, dedicated schemes derived these expected play important role transition domain servers mobile devices.