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    ELECTRONIC APPARATUS AND METHOD FOR CONTROLLING THEREOF
    1.
    发明申请
    ELECTRONIC APPARATUS AND METHOD FOR CONTROLLING THEREOF 有权

    公开(公告)号：US20220058487A1

    公开(公告)日：2022-02-24

    申请号：US17520326

    申请日：2021-11-05

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Dongsoo LEE ,  Sejung KWON ,  Byeoungwook Kim

    IPC: G06N3/08 ,  G06K9/62

    Abstract: An electronic apparatus, including a memory configured to store weight data used for computation of a neural network model; and a processor configured to: identify, from among weight values included in the weight data, at least one weight value having a size less than or equal to a threshold value, quantize remaining weight values other than the identified at least one weight value to obtain first quantized data including quantized values corresponding to the remaining weight values, identify, from among the quantized values, a quantized value closest to a predetermined value, obtain second quantized data including a quantized value corresponding to the at least one weight value based on the quantized value closest to the predetermined value, and store the first quantized data and the second quantized data in the memory

    Electronic apparatus and control method thereof
    2.
    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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