METHOD AND APPARATUS FOR DETERMINING CANDIDATE MEMBER, AND DEVICE

    公开(公告)号:US20250023785A1

    公开(公告)日:2025-01-16

    申请号:US18897785

    申请日:2024-09-26

    Abstract: This application discloses a method and an apparatus for determining a candidate member, and a device. The method for determining a candidate member in embodiments of this application includes: receiving, by a first network element, a request message sent by a second network element, where the request message includes filter information; determining, by the first network element based on the filter information, one or more first devices as candidate member(s) able to participate in federated learning; and sending, by the first network element, a response message to the second network element, where the response message includes an identifier of the candidate member, and the filter information includes at least one of the following: a time window, an algorithm type, an accuracy threshold, a wireless access type, a signal quality requirement, a traffic range, member type information, quantity information, area information, and federated learning type information.

    FEDERATED LEARNING METHOD AND APPARATUS, COMMUNICATION DEVICE, AND READABLE STORAGE MEDIUM

    公开(公告)号:US20250148297A1

    公开(公告)日:2025-05-08

    申请号:US19012169

    申请日:2025-01-07

    Inventor: Sihan CHENG

    Abstract: This application discloses a federated learning method and apparatus, a communication device, and a readable storage medium. The federated learning method of embodiments of this application includes: receiving, by a first communication device, first information from a second communication device, where the first information includes at least one of the following: second information used for indicating whether the second communication device agrees to participate in federated learning, status information of the second communication device in a current round of federated learning, and model performance information of a current round of federated learning; and determining, based on the first information, whether the second communication device participates in a next round of federated learning.

    MODEL ACQUISITION METHOD AND COMMUNICATION DEVICE

    公开(公告)号:US20250063406A1

    公开(公告)日:2025-02-20

    申请号:US18937061

    申请日:2024-11-05

    Abstract: Provided are a model obtaining method and a communication device. The method includes: sending, by a first communication device, a first request to a second communication device, where the first request is used to request to obtain information of at least one third communication device, and each third communication device is able to provide model information of at least one model required by the first communication device; receiving, by the first communication device, information of at least one third communication device that is sent by the second communication device; and obtaining, by the first communication device, model information of a plurality of models based on the information of the at least one third communication device, where the plurality of models are used to derive data analytics result information.

    MODEL ACCURACY DETERMINING METHOD AND APPARATUS, AND NETWORK-SIDE DEVICE

    公开(公告)号:US20240428094A1

    公开(公告)日:2024-12-26

    申请号:US18823861

    申请日:2024-09-04

    Abstract: This application discloses a model accuracy determining method and apparatus, and a network-side device. A model accuracy determining method in an embodiment of this application includes: performing, by a first network element, inference for a task based on a first model; determining, by the first network element, first accuracy corresponding to the first model, where the first accuracy is used to indicate accuracy of an inference result of the task obtained by the first model; and in a case that the first accuracy meets a preset condition, sending, by the first network element, first information to a second network element, where the first information is used to indicate that accuracy of the first model does not meet an accuracy requirement or has decreased; where the second network element is a network element that triggers the task.

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