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Found 2 papers, 1 papers with code
DACFL: Dynamic Average Consensus Based Federated Learning in Decentralized Topology
Federated learning (FL) is a burgeoning distributed machine learning framework where a central parameter server (PS) coordinates many local users to train a globally consistent model.
Semi-Federated Learning
Federated learning (FL) enables massive distributed Information and Communication Technology (ICT) devices to learn a global consensus model without any participants revealing their own data to the central server.
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