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公开(公告)号：US20220092475A1
公开(公告)日：2022-03-24
申请号：US17419974
申请日：2019-01-11
Applicant: NEC Corporation
Inventor： Yasuhiro SOGAWA , Tomoya SAKAI
Abstract: A target task attribute estimation unit 81 estimates an attribute vector of an existing predictor based on samples in a domain of a target task, and estimates an attribute vector of the target task based on a transformation method for transforming labeled samples into a space consisting of the estimated attribute vector based on a result of applying the labeled samples of the target task to the predictor. A prediction value calculation unit 82 calculates a prediction value of a prediction target sample to be transformed by the transformation method based on the attribute vector of the target task.
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公开(公告)号：US20220027760A1
公开(公告)日：2022-01-27
申请号：US17297181
申请日：2018-12-10
Applicant: NEC Corporation
Inventor： Tomoya SAKAI , Yasuhiro SOGAWA
Abstract: A learning device 100 includes correspondence inference unit which calculates outputs of predictors, which have learned for seen tasks or seen classes, for test input data, and infers correspondences between the calculated outputs and attribute information corresponding to an unseen task or an unseen class, and prediction unit which calculates a prediction output for the attribute information corresponding to the unseen task or the unseen class, using the inferred correspondences.
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3.发明申请公开(公告)号：US20200027044A1
公开(公告)日：2020-01-23
申请号：US16497858
申请日：2017-03-31
Applicant: NEC Corporation
Inventor： Yasuhiro SOGAWA , Nobuhiro MIKAMI
Abstract: In order to supplement results of diagnosis of degradation of an object that has been implemented at set intervals using a degradation progression model for simulating the progression of degradation of the object, a degradation prediction apparatus 100 is provided with: a data generation unit 112 configured to generate, as supplement data, diagnosis results that would be obtained if the degradation diagnosis were performed at an interval shorter than the set interval; a prediction model generation unit 113 configured, using the supplement data, to generate a prediction model for predicting a degradation index indicating a degradation state of the object at a specific point in time; and a degradation index prediction unit 114 configured to predict the degradation index of the object based on the prediction model.
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Patent Agency Ranking
公开(公告)号：US20180075360A1
公开(公告)日：2018-03-15
申请号：US15560085
申请日：2016-03-08
Applicant: NEC CORPORATION
Inventor： Akira TANIMOTO , Junpei KOMIYAMA , Yousuke MOTOHASHI , Ryohei FUJIMAKI , Yasuhiro SOGAWA
Abstract: An accuracy estimation unit 91 estimates accuracy of a predictive model using an accuracy estimating model that is learned using, as an explanatory variable, all or part of one or more contexts each indicating a feature value representing an operation status of the predictive model at a first point of interest that is a past point in time of interest a learning period of the predictive model, and a parameter used to learn the predictive model and, as a response variable, an accuracy index in a period after the first point of interest. The accuracy estimation unit 91 calculates the context at a second point of interest that is a point in time after the first point of interest, and applies the calculated context to the accuracy estimating model to estimate the accuracy from the second point of interest onward.
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5.发明申请公开(公告)号：US20220092622A1
公开(公告)日：2022-03-24
申请号：US17420026
申请日：2019-01-10
Applicant: NEC Corporation
Inventor： Tomoya SAKAI , Yasuhiro SOGAWA
Abstract: The learning unit 81 learns an attribute viewpoint model in which attributes of a target are explanatory variables for each target person so as to minimize a difference between a prediction result by a predictor that predicts an evaluation result of each target person based on a feature vector of the target person and a prediction result by a prediction model that predicts an evaluation result learned for each target person, using the attributes of the target as explanatory variables. The attribute generation unit 82 generates an attribute so that an evaluation result obtained according to the attribute applied to the learned prediction model satisfies the specified objective.
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公开(公告)号：US20210056449A1
公开(公告)日：2021-02-25
申请号：US17044530
申请日：2018-07-25
Applicant: NEC CORPORATION
Inventor： Yasuhiro SOGAWA , Akihiro YABE
Abstract: A query specification unit 81 specifies a query as a combination of a variable, on which an intervention operation is performed for a causal relation, and a value of the variable. An intervention data generating unit 82 generates intervention data including a value of a target variable, acquired with an intervention operation based on the query, and the query. A causal relation updating unit 83 updates the causal relation using the generated intervention data. On this occasion, the query specification unit 81 specifies a query that minimizes an expected loss by updating from among queries specified based on the expected loss representing an estimation error of the target variable by the query.
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公开(公告)号：US20170276567A1
公开(公告)日：2017-09-28
申请号：US15456727
申请日：2017-03-13
Applicant: NEC Corporation
Inventor： Yasuhiro SOGAWA , Nobuhiro MIKAMI
IPC: G01M5/00
CPC classification number: G01M5/0033 , G01M5/0008 , G06N5/04 , G06Q10/20 , G06Q50/08
Abstract: An information processing apparatus comprises: a processor configured to: estimate a soundness degree of a checkup-object structure from an inspection result of the checkup-object structure, based on a model generated by using an inspection result of a learning-object structure and a soundness degree of the learning-object structure; and present in a recognizable manner an erroneous determination possibility indicating a possibility that a soundness degree determined from the inspection result of the checkup-object structure is erroneous, based on the estimated soundness degree of the checkup-object structure.
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8.发明申请FEATURE-CONVERTING DEVICE, FEATURE-CONVERSION METHOD, LEARNING DEVICE, AND RECORDING MEDIUM 审中-公开特征转换装置，特征转换方法，学习装置和记录介质公开(公告)号：US20170076211A1
公开(公告)日：2017-03-16
申请号：US15122461
申请日：2015-03-03
Applicant: NEC Corporation
Inventor： Yukitaka KUSUMURA , Ryohei FUJIMAKI , Yasuhiro SOGAWA , Satoshi MORINAGA
Abstract: A feature-converting device that provides good features quickly. The device includes first and second feature construction units and first and second feature selection units. The first feature construction unit receives one or more first features and constructs one or more second features that represent the results of applying a unary function to the respective first features. The first feature selection unit computes relevance between the first and second features and a target variable that includes elements associated with elements included in the first features and selects one or more third features that represent highly relevant features. The second feature construction unit constructs one or more fourth features that represent the results of applying a multi-operand function to the third features. The second feature selection unit computes the relevance between the third and fourth features and the target variable and selects at least one fifth feature that represents highly relevant features.
Abstract translation: 功能转换设备快速提供良好的功能。 该装置包括第一和第二特征构造单元以及第一和第二特征选择单元。 第一特征构造单元接收一个或多个第一特征并构造表示将一元函数应用于相应的第一特征的结果的一个或多个第二特征。 第一特征选择单元计算第一和第二特征之间的相关性以及包括与包括在第一特征中的元素相关联的元素的目标变量，并且选择表示高度相关特征的一个或多个第三特征。 第二特征构造单元构造表示将多操作数函数应用于第三特征的结果的一个或多个第四特征。 第二特征选择单元计算第三和第四特征与目标变量之间的相关性，并且选择表示高度相关特征的至少一个第五特征。
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