PRIVACY PRESERVING TRANSFER LEARNING
    1.
    发明公开

    公开(公告)号:US20240273401A1

    公开(公告)日:2024-08-15

    申请号:US18169011

    申请日:2023-02-14

    Applicant: Google LLC

    CPC classification number: G06N20/00 G06F21/6218

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training and using machine learning models to predict data in privacy preserving manners are described. In one aspect, a method includes receiving, from a client device of a user, a digital component request including one or more contextual signals that describe an environment in which a selected digital component will be presented. The contextual signals are provided as input to a trained machine learning model that is trained to output, based on input contextual signals, predicted data about the user. The trained machine learning model is trained using a set of aggregated data including, for each of a set of aggregation keys, aggregated data for a plurality of users having electronic resource views that match the aggregation key. The predicted data about the user is received as an output of the trained machine learning model.

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