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    SUGGESTING EXECUTABLE ACTIONS IN RESPONSE TO DETECTING EVENTS
    2.
    发明公开
    SUGGESTING EXECUTABLE ACTIONS IN RESPONSE TO DETECTING EVENTS 审中-公开

    公开(公告)号：EP4400966A3

    公开(公告)日：2024-10-09

    申请号：EP24178160.8

    申请日：2021-05-27

    申请人： Apple Inc.

    发明人： AGGARWAL, Akshay ,  RAMASWAMY, Pallavika

    IPC分类号： G06F9/451 ,  G06N3/00 ,  G06N3/08 ,  G06N5/01 ,  G06N5/02 ,  G06N3/04 ,  G06N20/00

    CPC分类号： G06F9/451 ,  G06N3/04 ,  G06N3/08 ,  G06N5/02 ,  G06N20/00 ,  G06N5/01

    摘要： Systems and processes for providing, via an electronic device, suggested user actions. The suggested actions are provided in response to detecting an occurrence of a predefined event occurring in the user's day. The occurrence of the anchor is encoded in signals generated by the electronic device. The occurrence of the anchor is detectable via monitoring and analysis of electronic signals. Based on the user's previous interactions with the device, the occurrence of the anchor is indicative of user behavior and/or action taken in response to the anchor. Machine learning (ML) is employed to train an anchor model to associate actions taken in response to anchor occurrences. The trained anchor model is employed to detect anchors and provide suggested actions in response to the detected anchor occurrence. The suggested action is based on a type of anchor occurrence and contextual conditions of the anchor occurrences.

    METHOD FOR PERFORMING FEDERATED LEARNING IN WIRELESS COMMUNICATION SYSTEM, AND APPARATUS THEREFOR
    5.
    发明公开
    METHOD FOR PERFORMING FEDERATED LEARNING IN WIRELESS COMMUNICATION SYSTEM, AND APPARATUS THEREFOR 审中-实审

    公开(公告)号：EP4398160A1

    公开(公告)日：2024-07-10

    申请号：EP21956131.3

    申请日：2021-09-01

    申请人： LG Electronics Inc.

    发明人： LEE, Taehyun ,  LEE, Sangrim ,  JUNG, Ikjoo ,  LEE, Hojae ,  KIM, Yeongjun ,  JEON, Kijun

    IPC分类号： G06N20/20 ,  G06N5/02

    CPC分类号： G06N5/02 ,  G06N20/20

    摘要： The present specification provides a method by which a plurality of terminals perform federated learning in a wireless communication system. More particularly, the method performed by one terminal comprises the steps of: receiving, from a base station, a first downlink signal for requesting information regarding learning data for the federated learning, which is used by the one terminal; transmitting, to the base station, the information regarding the learning data on the basis of a type of learning data, the information regarding the learning data being information related to the distribution of the learning data used by the one terminal; receiving, from the base station, a second downlink signal including parameter information regarding a parameter related to a configuration for performing the federated learning, which has been determined on the basis of the learning data; and performing the federated learning on the basis of the information regarding the parameter.

    METHOD AND DEVICES FOR MONITORING PERFORMANCE DATA OF AN AI MODEL
    9.
    发明公开
    METHOD AND DEVICES FOR MONITORING PERFORMANCE DATA OF AN AI MODEL 审中-实审

    公开(公告)号：EP4365779A1

    公开(公告)日：2024-05-08

    申请号：EP22205446.2

    申请日：2022-11-04

    申请人： Helsing GmbH

    发明人： ADLER, Antonia ,  WANKA, Jean-Marc ,  KRAH, Moritz

    IPC分类号： G06N20/00 ,  G06N5/02 ,  G06N5/04 ,  G06F11/34

    CPC分类号： G06N5/04 ,  G06N5/02 ,  G06N20/00 ,  G06F11/0754 ,  G06F2201/8120130101

    摘要： There is provided a method, systems and devices for monitoring (110) performance data of an algorithm and/or artificial intelligence, AI, model deployed on a platform; determining (120, 240) one or more performance criteria for the algorithm and/or AI model; comparing (130) the monitored performance data to the one or more performance criteria; triggering (140) an alert event based on the comparison of the monitored data to the one or more performance criteria; characterized in that the one or more performance criteria are determined based on a predetermined set of rules provided by a central server communicatively coupled to the platform, the set of rules being associated with the algorithm, the AI model and/or the platform.