1.7k citations · 2.8k across the 3 of their papers we have counts for
3 papers
Towards Federated Learning at Scale: System Design
Keith Bonawitz, Hubert Eichner, Wolfgang Grieskamp +11
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 F…
Practical Secure Aggregation for Federated Learning on User-Held Data
Keith Bonawitz, Vladimir Ivanov, Ben Kreuter +6
Secure Aggregation protocols allow a collection of mutually distrust parties, each holding a private value, to collaboratively compute the sum of those values without revealing the…
Federated Optimization: Distributed Machine Learning for On-Device Intelligence
Jakub Konečný, H. Brendan McMahan, Daniel Ramage +1
We introduce a new and increasingly relevant setting for distributed optimization in machine learning, where the data defining the optimization are unevenly distributed over an ext…