LABEL INFERENCE IN SPLIT LEARNING DEFENSES
    1.
    发明公开

    公开(公告)号:US20230143789A1

    公开(公告)日:2023-05-11

    申请号:US18149462

    申请日:2023-01-03

    Applicant: Lemon Inc.

    CPC classification number: G06N3/084 G06N3/045

    Abstract: Split learning is provided to train a composite neural network (CNN) model that is split into first and second submodels, including receiving a noise-laden backpropagation gradient, training the surrogate submodel by optimizing a gradient distance loss, and computing an updated dummy label using the first submodel and the trained surrogate submodel to infer label information of the second submodel. Noise can be added to a label of the second submodel or a shared backpropagation gradient to protect the label information.

Patent Agency Ranking