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公开(公告)号：US20220245518A1
公开(公告)日：2022-08-04
申请号：US17610488
申请日：2019-05-22
Applicant: NEC Corporation
Inventor： Masato ISHII , Takashi TAKENOUCHI , Masashi SUGIYAMA
Abstract: A data transformation apparatus (1) includes: data transformation means (11) for performing data transformation on each of a plurality of data sets so that data distributions of the plurality of data sets are brought close to each other; first calculation means (12) for calculating a class classification loss from a result of class classification performed by class classification means on at least some of a plurality of first transformed data sets obtained after the data transformation; second calculation means (13) for calculating an upper bound and a lower bound of a domain classification loss from a result of domain classification performed by domain classification means on each of the plurality of first transformed data sets; and first learning means (14) for performing first learning by updating a parameter of the domain classification means so that the upper bound is reduced and updating a parameter of the data transformation means so that the class classification loss is reduced and the lower bound is increased.
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公开(公告)号：US20220121990A1
公开(公告)日：2022-04-21
申请号：US17422678
申请日：2019-01-22
Applicant: NEC Corporation
Inventor： Masato ISHII , Takashi TAKENOUCHI , Masashi SUGIYAMA
Abstract: A data conversion learning apparatus includes a data conversion unit that performs data conversion of source data and target data, a first deduction unit that deduces data of a non-appearing class on the basis of a domain certainty factor acquired by a domain identification using converted data, a second deduction unit that deduces data of a non-appearing class on the basis of a class certainty factor acquired by a class identification using converted data, a class identification learning unit that performs machine learning for class identification using the data of the non-appearing class deduced by the first deduction unit and the source data and the target data which are inputs, and a domain identification learning unit that performs machine learning for domain identification using the data of the non-appearing class deduced by the second deduction unit and the source data and the target data which are inputs.
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公开(公告)号：US20210019636A1
公开(公告)日：2021-01-21
申请号：US17043309
申请日：2018-05-11
Applicant: NEC Corporation
Inventor： Masato ISHII , Takashi TAKENOUCHI , Masashi SUGIYAMA
Abstract: This prediction model preparation device is provided with: a calculation means which calculates, from a datum in which a sample and a label are associated with each other, an importance level according to the difference between a first possibility that an event influencing the sample occurs in a source domain and a second possibility that the event occurs in a target domain; and a preparation means which constructs prepares a prediction model relating to the target domain by calculating association between the sample and the label included in the datum to which the importance level is added.
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