1.1k citations · 2.8k across the 9 of their papers we have counts for
7 papers · 1 filter
Federated Learning in Practice: Reflections and Projections
Katharine Daly, Hubert Eichner, Peter Kairouz +3
Federated Learning (FL) is a machine learning technique that enables multiple entities to collaboratively learn a shared model without exchanging their local data. Over the past de…
Federated Training of Dual Encoding Models on Small Non-IID Client Datasets
Raviteja Vemulapalli, Warren Richard Morningstar, Philip Andrew Mansfield +4
Dual encoding models that encode a pair of inputs are widely used for representation learning. Many approaches train dual encoding models by maximizing agreement between pairs of e…
A Field Guide to Federated Optimization
Jianyu Wang, Zachary Charles, Zheng Xu +50
Federated learning and analytics are a distributed approach for collaboratively learning models (or statistics) from decentralized data, motivated by and designed for privacy prote…
Federated Evaluation of On-device Personalization
Kangkang Wang, Rajiv Mathews, Chloé Kiddon +3
Federated learning is a distributed, on-device computation framework that enables training global models without exporting sensitive user data to servers. In this work, we describe…
Semi-Cyclic Stochastic Gradient Descent
Hubert Eichner, Tomer Koren, H. Brendan McMahan +2
We consider convex SGD updates with a block-cyclic structure, i.e. where each cycle consists of a small number of blocks, each with many samples from a possibly different, block-sp…
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…
Applied Federated Learning: Improving Google Keyboard Query Suggestions
Timothy Yang, Galen Andrew, Hubert Eichner +5
Federated learning is a distributed form of machine learning where both the training data and model training are decentralized. In this paper, we use federated learning in a commer…