Web: http://arxiv.org/abs/2207.04330

Sept. 22, 2022, 1:13 a.m. | Neelkamal Bhuyan, Sharayu Moharir, Gauri Joshi

stat.ML updates on arXiv.org arxiv.org

Federated Learning (FL) is a variant of distributed learning where edge
devices collaborate to learn a model without sharing their data with the
central server or each other. We refer to the process of training multiple
independent models simultaneously in a federated setting using a common pool of
clients as multi-model FL. In this work, we propose two variants of the popular
FedAvg algorithm for multi-model FL, with provable convergence guarantees. We
further show that for the same amount of …

arxiv federated learning

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