TRAINING NEURAL NETWORKS WITH LABEL DIFFERENTIAL PRIVACY

    公开(公告)号:US20220129760A1

    公开(公告)日:2022-04-28

    申请号:US17511448

    申请日:2021-10-26

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training neural networks with label differential privacy. One of the methods includes, for each training example: processing the network input in the training example using the neural network in accordance with the values of the network parameters as of the beginning of the training iteration to generate a network output, generating a private network output for the training example from the target output in the training example and the network output for the training example, and generating a modified training example that includes the network input in the training example and the private network output for the training example; and training the neural network on at least the modified training examples to update the values of the network parameters.

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