Search Results for author: Hubert Eichner

Found 9 papers, 7 papers with code

Federated Training of Dual Encoding Models on Small Non-IID Client Datasets

no code implementations30 Sep 2022 Raviteja Vemulapalli, Warren Richard Morningstar, Philip Andrew Mansfield, Hubert Eichner, Karan Singhal, Arash Afkanpour, Bradley Green

In this work, we focus on federated training of dual encoding models on decentralized data composed of many small, non-IID (independent and identically distributed) client datasets.

Federated Learning Representation Learning

Federated Evaluation of On-device Personalization

1 code implementation22 Oct 2019 Kangkang Wang, Rajiv Mathews, Chloé Kiddon, Hubert Eichner, Françoise Beaufays, Daniel Ramage

Federated learning is a distributed, on-device computation framework that enables training global models without exporting sensitive user data to servers.

Language Modelling

Semi-Cyclic Stochastic Gradient Descent

no code implementations23 Apr 2019 Hubert Eichner, Tomer Koren, H. Brendan McMahan, Nathan Srebro, Kunal Talwar

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-specific, distribution.

Federated Learning

Federated Learning for Mobile Keyboard Prediction

5 code implementations8 Nov 2018 Andrew Hard, Kanishka Rao, Rajiv Mathews, Swaroop Ramaswamy, Françoise Beaufays, Sean Augenstein, Hubert Eichner, Chloé Kiddon, Daniel Ramage

We train a recurrent neural network language model using a distributed, on-device learning framework called federated learning for the purpose of next-word prediction in a virtual keyboard for smartphones.

Federated Learning Language Modelling

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