Towards Federated Learning at Scale: System Design
Towards Federated Learning at Scale: System Design
Keith Bonawitz,Hubert Eichner,11 Authors,Jason Roselander
2019 · ArXiv: 1902.01046
USENIX workshop on Tackling computer systems problems with machine learning techniques · 3,114 Citations
TLDR
A scalable production system for Federated Learning in the domain of mobile devices, based on TensorFlow is built, describing the resulting high-level design, and sketch some of the challenges and their solutions.
Abstract
Federated Learning is a distributed machine learning approach which enables model training on a large corpus of decentralized data. We have built a scalable production system for Federated Learning in the domain of mobile devices, based on TensorFlow. In this paper, we describe the resulting high-level design, sketch some of the challenges and their solutions, and touch upon the open problems and future directions.