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公开(公告)号：US20140344183A1
公开(公告)日：2014-11-20
申请号：US13898118
申请日：2013-05-20
Applicant: Nec Corporation
Inventor： Ryohei FUJIMAKI , Kouhei HAYASHI
IPC: G06Q10/06
CPC classification number: G06Q10/067 , G06F17/18 , G06N7/005 , G06Q10/063
Abstract: An approximate computation unit computes an approximate of a determinant of a Hessian matrix relating to observed data represented as a matrix. A variational probability computation unit computes a variational probability of a latent variable using the approximate of the determinant. A latent state removal unit removes a latent state based on a variational distribution. A parameter optimization unit optimizes a parameter for a criterion value that is defined as a lower bound of an approximate obtained by Laplace-approximating a marginal log-likelihood function with respect to an estimator for a complete variable, and computes the criterion value. A convergence determination unit determines whether or not the criterion value has converged.
Abstract translation: 近似计算单元计算与以矩阵表示的观测数据相关的Hessian矩阵的行列式的近似值。 变分概率计算单元使用行列式的近似来计算潜在变量的变分概率。 潜在去除单元基于变分分布去除潜在状态。 参数优化单元优化一个标准值的参数，该标准值被定义为通过拉普拉斯近似边界对数似然函数相对于完整变量的估计器获得的近似值的下限，并计算标准值。 收敛确定单元确定标准值是否收敛。
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公开(公告)号：US20190311222A1
公开(公告)日：2019-10-10
申请号：US16345496
申请日：2017-10-18
Applicant: NEC CORPORATION
Inventor： Shinji ITO , Akihiro YABE , Ryohei FUJIMAKI
Abstract: An evaluation system 80 includes an evaluation unit 81 for evaluating, when there is a prediction model estimated using data generated from the true model, the optimal solution calculated from the prediction model in consideration of bias generated between evaluation based on the prediction model and evaluation based on the true model.
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公开(公告)号：US20190220496A1
公开(公告)日：2019-07-18
申请号：US16301662
申请日：2017-05-01
Applicant: NEC CORPORATION
Inventor： Shinji ITO , Ryohei FUJIMAKI
Abstract: An accepting unit 81 accepts an optimization problem that can be formulated as BQP represented by zTAz+bTz by use of an n×n square matrix A and an n-dimensional vector b. A condition storage unit 82 stores characteristic conditions representing characteristics of a positive weighted directed graph. An optimization unit 83 transforms the optimization problem based on the characteristic conditions, and solves the accepted optimization problem by solving the transformed problem as a minimum cut problem of a network flow.
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公开(公告)号：US20180349738A1
公开(公告)日：2018-12-06
申请号：US15731172
申请日：2015-10-16
Applicant: NEC CORPORATION
Inventor： Ryohei FUJIMAKI , Hidekazu OIWA
CPC classification number: G06K9/6219 , G06F17/18 , G06K9/6226 , G06N20/00
Abstract: A region linear model optimization system optimizes a region linear model, and includes: a linear model setting unit 81 for setting for a partition a linear model to be applied to one of regions representing subspaces divided by the partition, the partition being an indicator function dividing an input space into two portions; and a region model calculation unit 82 for representing a model of each of the regions in the region linear model as a linear combination of the linear models to be applied to the respective regions.
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25.发明申请公开(公告)号：US20180225681A1
公开(公告)日：2018-08-09
申请号：US15750349
申请日：2016-07-26
Applicant: NEC CORPORATION
Inventor： Ryohei FUJIMAKI , Takeshi ISHIHARA
CPC classification number: G06Q30/0201 , G06N20/00 , G06Q10/10
Abstract: Provided is a user information estimation system capable of estimating demographic information about a user of a prepaid mobile terminal. An estimation model generation means 21 generates, on the basis of information relating to a mobile terminal in which demographic information about a user is known, and the demographic information, an estimation model with demographic information as an objective variable, and information relating to a mobile terminal as an explanatory variable. An estimation means 22 applies information relating to a prepaid mobile terminal to the estimation model, to calculate an estimated value of demographic information about a user of the prepaid mobile terminal.
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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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27.发明申请公开(公告)号：US20180012128A1
公开(公告)日：2018-01-11
申请号：US15544309
申请日：2016-01-18
Applicant: NEC Corporation
Inventor： Yuki CHIBA , Yousuke MOTOHASHI , Ryohei FUJIMAKI , Satoshi MORINAGA
Abstract: An explanatory variable display means 81 extracts an explanatory variable used as a condition from a classification model classified by the condition for selecting a component used for prediction and displays the explanatory variable in association with any of dimensional axes of a multi-dimensional space in which a prediction value is displayed. A prediction value display means 82 specifies the component that corresponds to a position in the multi-dimensional space specified by each of the explanatory variables associated with the dimensional axis, and then, displays the prediction value calculated on the basis of the specified component, on the same position. A space display means 83 displays the multi-dimensional space that corresponds to the position in which the prediction value is displayed, in a mode that corresponds to the component used for calculating the prediction value.
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公开(公告)号：US20170206560A1
公开(公告)日：2017-07-20
申请号：US15326273
申请日：2015-06-26
Applicant: NEC Corporation
Inventor： Yukitaka KUSUMURA , Hironori MIZUGUCHI , Ryohei FUJIMAKI , Satoshi MORINAGA
IPC: G06Q30/02
CPC classification number: G06Q30/0264 , G06Q30/02 , G06Q30/0202 , G06Q30/0242
Abstract: A prediction data input unit 91 inputs prediction data that is one or more explanatory variables that are information likely to affect future sales. An exposure pattern generation unit 92 generates an exposure pattern which is an explanatory variable indicating the content of a commercial message scheduled to be performed during a period from predicted time to future prediction target time. A component determination unit 93 determines the component used for predicting the sales, on the basis of a hierarchical latent structure that is a structure in which latent variables are represented by a tree structure and components representing probability models are located at nodes of a lowest level of the tree structure, gating functions for determining a branch direction in the nodes of the hierarchical latent structure, and the prediction data and the exposure pattern. A sales prediction unit 94 predicts the sales on the basis of the component determined by the component determination unit 93 and of the prediction data and the exposure pattern.
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29.发明申请公开(公告)号：US20170148196A1
公开(公告)日：2017-05-25
申请号：US15323290
申请日：2015-06-03
Applicant: Nec Corporation
Inventor： Yusuke MURAOKA , Ryohei FUJIMAKI
CPC classification number: G06T11/206 , G06F13/00 , G06F17/30958 , G06N5/04 , G06Q30/0269
Abstract: Provided is a feature-value display system which can display a feature value of a node for accurate prediction of a state of the node in a graph structure or a network structure. The feature-value display system 1 displays the feature value of the current node, considering information generated on the basis of attribute information associated with the nodes adjacent to or closer to a current node in the graph structure or the network structure, as the feature value of the current node itself.
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公开(公告)号：US20170140401A1
公开(公告)日：2017-05-18
申请号：US15323280
申请日：2015-06-04
Applicant: NEC Corporation
Inventor： Yusuke MURAOKA , Ryohei FUJIMAKI
CPC classification number: G06Q30/0202 , G06N7/005 , G06N20/00
Abstract: From learning data that expresses inter-node connection relationships that are expressed as a graph structure or a network structure, a vicinal node information acquisition unit 81 acquires edge information that indicates the connection relationship between one node and another node to which the one node connects. Using the acquired edge information and node feature information that indicates the features of the other node, a feature value calculation unit 82 calculates a feature value that is for the one node and that is to be used for prediction.
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