INFORMATION PROCESSING APPARATUS
    1.
    发明申请

    公开(公告)号:US20220253507A1

    公开(公告)日:2022-08-11

    申请号:US17630621

    申请日:2019-08-02

    Inventor: Yuta IDEGUCHI

    Abstract: A first transforming unit divides a sparse matrix into a first submatrix including a row in which the number of non-zero elements is a predetermined number or more and a second submatrix including a row other than the row, and transforms the first submatrix into a row-major order dense matrix format. A second transforming unit divides the second submatrix into a third submatrix including a column in which the number of non-zero elements is a predetermined number or more and a fourth submatrix including a column other than the column, and transforms the third submatrix into a column-major order dense matrix format. A third transforming unit divides the fourth submatrix into a fifth submatrix and a sixth submatrix, and transforms the fifth submatrix into a row-major order sparse matrix compression format. A fourth transforming unit transforms the sixth submatrix into a column-major order sparse matrix compression format.

    WEIGHT COEFFICIENT CALCULATION DEVICE AND WEIGHT COEFFICIENT CALCULATION METHOD

    公开(公告)号:US20250165668A1

    公开(公告)日:2025-05-22

    申请号:US18841728

    申请日:2022-04-22

    Inventor: Yuta IDEGUCHI

    Abstract: Each constraint term in an expression representing energy in a combinatorial optimization problem is input the input means 71. The automatic establishment rate calculation means 73 calculates an automatic establishment rate for each constraint term, wherein the automatic establishment rate is a probability that a constraint represented by a constraint term is satisfied when all other constraints associated with individual spins associated with the constraint term are satisfied. The energy increase amount determination means 74 determines amount of energy increase at constraint breakdown for each constraint term, wherein the amount of energy increase at constraint breakdown is amount of energy increase when a constraint represented by a constraint term is no longer satisfied. The spin number derivation means 75 derives the number of spins associated with a constraint represented by a constraint term, for each constraint term.

    SIMULATED ANNEALING DEVICE AND SIMULATED ANNEALING METHOD

    公开(公告)号:US20240202392A1

    公开(公告)日:2024-06-20

    申请号:US18287098

    申请日:2021-04-28

    Inventor: Yuta IDEGUCHI

    CPC classification number: G06F30/20

    Abstract: A simulated annealing device for solving a combinatorial optimization problem by a simulated annealing scheme includes a confirmation unit which executes a process of confirming whether a flip is accepted or not for each of n spins from {(k−1)·n+1}-th to k·n-th that constitute an energy function in the Ising model representing the combinatorial optimization problem in parallel with a parallel number n, an updating unit which, when the acceptance of a flip on m-th spin (m is an integer between {(k−1)·n+1} and k·n) is confirmed first, updates change amount in energy of a spin associated with the m-th spin with the m-th spin flipped, and a changing unit which changes spins in which the next process of confirming is executed and the parallel number to spins from (m+1)-th to k·n-th and (n−m), respectively.

    INFORMATION PROCESSING METHOD
    5.
    发明申请

    公开(公告)号:US20230050883A1

    公开(公告)日:2023-02-16

    申请号:US17794007

    申请日:2020-02-05

    Inventor: Yuta IDEGUCHI

    Abstract: An information processing system according to the present invention is an information processing system that sets a weight matrix. The weight matrix is generated by learning using a target matrix that is a matrix including an action status on an item in each of a plurality of setting statuses as an element of a column, includes a weight corresponding to an intersection of items as an element, and is multiplied by the target matrix. The information processing system includes: a similarity degree calculating unit configured to extract, from each column of the target matrix, some elements from among all elements of the column, and calculate a degree of similarity between the items based on the some elements of the each column; and a weight matrix setting unit configured to set the weight matrix that is a sparse matrix including a nonzero element based on the degree of similarity.

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