Decentralized Federated Learning: A Segmented Gossip Approach

21 Aug 2019Chenghao HuJingyan JiangZhi Wang

The emerging concern about data privacy and security has motivated the proposal of federated learning, which allows nodes to only synchronize the locally-trained models instead their own original data. Conventional federated learning architecture, inherited from the parameter server design, relies on highly centralized topologies and the assumption of large nodes-to-server bandwidths... (read more)

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