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arxiv:1902.01046
Towards Federated Learning at Scale: System Design
Published on Mar 22, 2019
Authors:
Abstract
A scalable production federated learning system for mobile devices built on TensorFlow is described, covering design, challenges, and future directions.
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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.
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