LEARNING DEVICE
    1.
    发明申请

    公开(公告)号:US20210295153A1

    公开(公告)日:2021-09-23

    申请号:US17184026

    申请日:2021-02-24

    Abstract: A learning device includes an encoding unit, a plurality of permutation units, a plurality of decoding units, a selection unit, and a learning unit. The encoding unit is configured generate an encoded word by encoding a transmission word. The permutation units are configured to permutate the encoded word according to different permutation manners to generate a plurality of permutated encoded words. The decoding units are configured to perform message passing decoding on the plurality of permutated encoded words, to generate a plurality of decoded words. The message passing decoding involves weighting of values of a word transmitted during the message passing decoding. The selection unit is configured to select one or more of the decoded words. The learning unit is configured to perform learning of weighting values of the weighting based on the transmission word and the selected one or more of the decoded words.

    INFORMATION PROCESSING APPARATUS AND INFORMATION PROCESSING METHOD

    公开(公告)号:US20220300676A1

    公开(公告)日:2022-09-22

    申请号:US17350506

    申请日:2021-06-17

    Abstract: An information processing apparatus has a constraint threshold value setting change unit configured to change a setting of a first constraint threshold value serving as a criterion when determining whether a constraint variable satisfies a constraint condition, and a search unit configured to search for the new constraint variable that satisfies the constraint condition based on the first constraint threshold value, wherein the constraint threshold value setting change unit is configured to update the first constraint threshold value based on the new constraint variable.

    INFORMATION PROCESSING APPARATUS AND INFORMATION PROCESSING METHOD

    公开(公告)号:US20240289692A1

    公开(公告)日:2024-08-29

    申请号:US18588490

    申请日:2024-02-27

    CPC classification number: G06N20/00

    Abstract: An information processing apparatus comprising processing circuitry, the processing circuitry configured to train a prediction model based on a data set in which a setting value of a parameter and an evaluation value of the setting value are combined, generate a second range narrower than a first range that is a maximum variable range of the setting value inputtable to the prediction model based on the data set and the trained prediction model, shift the second range to include a center value of the first range, and calculate a new setting value to be evaluated next, based on an acquisition function optimized by inputting the setting value within the shifted second range to the trained prediction model.

    MEMORY SYSTEM
    5.
    发明申请

    公开(公告)号:US20210279133A1

    公开(公告)日:2021-09-09

    申请号:US17184166

    申请日:2021-02-24

    Abstract: A memory system includes a non-volatile memory and a memory controller. The memory controller is configured to read a received word from the non-volatile memory, estimate noise by using a plurality of different models for estimating the noise included in the received word to obtain a plurality of noise estimation values, select one noise estimation value from the plurality of noise estimation values, update the received word by using a value obtained by subtracting the selected noise estimation value from the read received word, and decode the updated received word by using a belief-propagation method.

    LEARNING DEVICE
    6.
    发明申请

    公开(公告)号:US20210242888A1

    公开(公告)日:2021-08-05

    申请号:US17005270

    申请日:2020-08-27

    Abstract: According to one embodiment, a learning device includes a noise generation unit, a decoding unit, a generation unit, and a learning unit. The noise generation unit outputs a second code word which corresponds to a first code word to which noise has been added. The decoding unit decodes the second code word and outputs a third code word. The generation unit generates learning data for learning a weight in message passing decoding in which the weight and a message to be transmitted are multiplied, based on whether or not decoding of the second code word into the third code word has been successful. The learning unit determines a value for the weight in the message passing decoding by using the learning data.

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