Federated Learning with Only Positive Labels

    公开(公告)号:US20210326757A1

    公开(公告)日:2021-10-21

    申请号:US17227851

    申请日:2021-04-12

    Applicant: Google LLC

    Abstract: Generally, the present disclosure is directed to systems and methods that perform spreadout regularization to enable learning of a multi-class classification model in the federated setting, where each user has access to the positive data associated with only a limited number of classes (e.g., a single class). Examples of such settings include decentralized training of face recognition models or speaker identification models, where in addition to the user specific facial images and voice samples, the class embeddings for the users also constitute sensitive information that cannot be shared with other users.

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