Asynchronous Federated Learning with non-convex client objective functions and heterogeneous dataset
Abstract: Federated Learning is a distributed machine learning paradigm that enables model training across decentralized devices holding local data, thereby preserving data privacy and reducing the ...
client and server are implemented in the same executable. the actual role (client or server) is decided by the subcommand. both client and server have the same optional CLI arguments: udp-echo-test ...
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