DISTRIBUTED MACHINE LEARNING WITH PRIVACY PROTECTION

    公开(公告)号:US20210056387A1

    公开(公告)日:2021-02-25

    申请号:US16545813

    申请日:2019-08-20

    Abstract: A system having multiple devices that can host different versions of an artificial neural network (ANN). In the system, changes to local versions of the ANN can be combined with a master version of the ANN. In the system, a first device can include memory that can store the master version, a second device can include memory that can store a local version of the ANN, and there can be many devices that store local versions of the ANN. The second device (or any other device of the system hosting a local version) can include a processor that can train the local version, and a transceiver that can transmit changes to the local version generated from the training. The first device can include a transceiver that can receive the changes to a local version, and a processing device that can combine the received changes with the master version.

    FEATURE DICTIONARY FOR BANDWIDTH ENHANCEMENT

    公开(公告)号:US20220309291A1

    公开(公告)日:2022-09-29

    申请号:US17841448

    申请日:2022-06-15

    Abstract: A system having multiple devices that can host different versions of an artificial neural network (ANN) as well as different versions of a feature dictionary. In the system, encoded inputs for the ANN can be decoded by the feature dictionary, which allows for encoded input to be sent to a master version of the ANN over a network instead of an original version of the input which usually includes more data than the encoded input. Thus, by using the feature dictionary for training of a master ANN there can be reduction of data transmission.

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