• Corpus ID: 236470180

# Federated Multi-Task Learning under a Mixture of Distributions

@article{Marfoq2021FederatedML,
title={Federated Multi-Task Learning under a Mixture of Distributions},
author={Othmane Marfoq and Giovanni Neglia and Aur{\'e}lien Bellet and Laetitia Kameni and Richard Vidal},
journal={ArXiv},
year={2021},
volume={abs/2108.10252}
}
• Published 23 August 2021
• Computer Science
• ArXiv
The increasing size of data generated by smartphones and IoT devices motivated the development of Federated Learning (FL), a framework for on-device collaborative training of machine learning models. First efforts in FL focused on learning a single global model with good average performance across clients, but the global model may be arbitrarily bad for a given client, due to the inherent heterogeneity of local data distributions. Federated multi-task learning (MTL) approaches can learn…
38 Citations

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