- K. A. Bonawitz
- Hubert Eichner
- Wolfgang Grieskamp
- Dzmitry Huba
- Alex Ingerman
- Vladimir Ivanov
- Chloé M Kiddon
- Jakub Konečný
- Stefano Mazzocchi
- Brendan McMahan
- Timon Van Overveldt
- David Petrou
- Daniel Ramage
- Jason Roselander
SysML 2019
Federated Learning is a distributed machine learning approach which enables training on a large corpus of data which never needs to leave user devices. We have spent some effort over the last two years building a scalable production system for FL. In this paper, we report about the resulting high-level design, sketching the challenges and the solutions, as well as touching the open problems and future directions.
We maintain a portfolio of research projects, providing individuals and teams the freedom to emphasize specific types of work