Web: http://arxiv.org/abs/2111.09360

June 20, 2022, 1:11 a.m. | Othmane Marfoq, Giovanni Neglia, Laetitia Kameni, Richard Vidal

cs.LG updates on arXiv.org arxiv.org

Federated learning allows clients to collaboratively learn statistical models
while keeping their data local. Federated learning was originally used to train
a unique global model to be served to all clients, but this approach might be
sub-optimal when clients' local data distributions are heterogeneous. In order
to tackle this limitation, recent personalized federated learning methods train
a separate model for each client while still leveraging the knowledge available
at other clients. In this work, we exploit the ability of deep …

arxiv federated learning learning lg personalized

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