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    ELECTRONIC DEVICE AND METHOD FOR CONTROLLING SAME
    3.
    发明公开
    ELECTRONIC DEVICE AND METHOD FOR CONTROLLING SAME 审中-公开

    公开(公告)号：US20230342602A1

    公开(公告)日：2023-10-26

    申请号：US18216824

    申请日：2023-06-30

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Jijoong Moon ,  Parichay Kapoor ,  Jihoon Lee ,  Geunsik Lim ,  Myungjoo Ham

    IPC: G06N3/08

    CPC classification number: G06N3/08

    Abstract: Disclosed are an electronic device including a memory and a processor, and a method for controlling same. The memory stores a pre-trained neural network model and training data. The processor obtains a first loss function based on a label corresponding to the training data and output data obtained by inputting the training data into the neural network model; obtains a size of a change amount of a weight of each of a plurality of layers included in the neural network model based on the first loss function, and trains the neural network model by updating a weight of at least one layer for which the magnitude of the change amount of the weight exceeds a first threshold value, while at least one other layer, among the plurality of layers, for which a size of the weight change amount does not exceed the first threshold value is not updated.

    Electronic apparatus and control method thereof
    5.
    发明授权
    Electronic apparatus and control method thereof 有权

    公开(公告)号：US11568254B2

    公开(公告)日：2023-01-31

    申请号：US16727323

    申请日：2019-12-26

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Dongsoo Lee ,  Sejung Kwon ,  Parichay Kapoor ,  Byeoungwook Kim

    IPC: G06N3/08 ,  G06F17/16 ,  G06N3/04

    Abstract: An electronic apparatus is provided. The electronic apparatus includes sample data and memory storing a first matrix included in an artificial intelligence model trained based on sample data, and a processor configured to prunes each of a plurality of first elements included in the first matrix based on a first threshold, and acquire a first pruning index matrix that indicates whether each of the plurality of first elements has been pruned with binary data, factorize the first matrix to a second matrix of which size was determined based on the number of rows and the rank, and a third matrix of which size was determined based on the rank and the number of columns of the first matrix, prunes each of a plurality of second elements included in the second matrix based on a second threshold, and acquire a second pruning index matrix that indicates whether each of the plurality of second elements has been pruned with binary data, prunes each of a plurality of third elements included in the third matrix based on a third threshold, and acquire a third pruning index matrix that indicates whether each of the plurality of third elements has been pruned with binary data, acquire a final index matrix based on the second pruning index matrix and the third pruning index matrix, and update at least one of the second pruning index matrix or the third pruning index matrix by comparing the final index matrix with the first pruning index matrix.

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