Federated Learning by Parameter Permutation
    1.
    发明公开

    公开(公告)号:US20240064016A1

    公开(公告)日:2024-02-22

    申请号:US18366586

    申请日:2023-08-07

    CPC classification number: H04L9/30 H04L9/14 G06N20/00

    Abstract: Parameter permutation is performed for federated learning to train a machine learning model. Parameter permutation is performed by client systems of a federated machine learning system on updated parameters of a machine learning model that have been updated as part of training using local training data. An intra-model shuffling technique is performed at the client systems according to a shuffling pattern. Then, the encoded parameters are provided to an aggregation server using Private Information Retrieval (PIR) queries generated according to the shuffling pattern.

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