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    HIERARCHICAL LATENT VARIABLE MODEL ESTIMATION DEVICE, HIERARCHICAL LATENT VARIABLE MODEL ESTIMATION METHOD, AND RECORDING MEDIUM
    41.
    发明申请
    HIERARCHICAL LATENT VARIABLE MODEL ESTIMATION DEVICE, HIERARCHICAL LATENT VARIABLE MODEL ESTIMATION METHOD, AND RECORDING MEDIUM 审中-公开
    分层可变模型估计装置，分层可变模型估计方法和记录介质

    公开(公告)号：US20150088804A1

    公开(公告)日：2015-03-26

    申请号：US14563227

    申请日：2014-12-08

    Applicant: NEC CORPORATION

    Inventor： Riki ETO ,  Ryohei FUJIMAKI ,  Satoshi MORINAGA

    IPC: G06N7/00

    CPC classification number: G06N7/005 ,  G06F17/18 ,  G06K9/00536 ,  G06N5/02 ,  G06N5/025

    Abstract: A hierarchical latent structure setting unit 81 sets 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. A variational probability computation unit 82 computes a variational probability of a path latent variable that is a latent variable included in a path linking a root node to a target node in the hierarchical latent structure. A component optimization unit 83 optimizes each of the components for the computed variational probability. A gating function optimization unit 84 optimizes a gating function model that is a model for determining a branch direction according to the multivariate data in a node of the hierarchical latent structure, on the basis of the variational probability of the latent variable in the node.

    Abstract translation: 分层潜在结构设置单元81设置作为其中潜变量由树结构表示的结构的分层潜在结构，并且表示概率模型的分量位于树结构的最底层的节点处。 变分概率计算单元82计算作为潜在变量的路径潜变量的变分概率，所述潜变量包括在将根节点链接到分层潜在结构中的目标节点的路径中。 分量优化单元83针对所计算的变分概率优化每个分量。 门控功能优化单元84基于节点中的潜在变量的变分概率来优化门控功能模型，门控功能模型是根据层级潜在结构的节点中的多变量数据确定分支方向的模型。

    HIERARCHICAL LATENT VARIABLE MODEL ESTIMATION DEVICE, HIERARCHICAL LATENT VARIABLE MODEL ESTIMATION METHOD, SUPPLY AMOUNT PREDICTION DEVICE, SUPPLY AMOUNT PREDICTION METHOD, AND RECORDING MEDIUM
    42.
    发明申请
    HIERARCHICAL LATENT VARIABLE MODEL ESTIMATION DEVICE, HIERARCHICAL LATENT VARIABLE MODEL ESTIMATION METHOD, SUPPLY AMOUNT PREDICTION DEVICE, SUPPLY AMOUNT PREDICTION METHOD, AND RECORDING MEDIUM 有权
    分层可变模型估计装置，分层可变模型估计方法，供应量预测装置，供应量预测方法和记录介质

    公开(公告)号：US20150088789A1

    公开(公告)日：2015-03-26

    申请号：US14032295

    申请日：2013-09-20

    Applicant: NEC Corporation

    Inventor： Yosuke MOTOHASHI ,  Satoshi MORINAGA ,  Ryohei FUJIMAKI ,  Riki ETO

    IPC: G06N5/02 ,  G06N99/00

    CPC classification number: G06N5/02 ,  G06N7/005 ,  G06N99/005

    Abstract: A hierarchical latent structure setting unit 81 sets 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. A variational probability computation unit 82 computes a variational probability of a path latent variable that is a latent variable included in a path linking a root node to a target node in the hierarchical latent structure. A component optimization unit 83 optimizes each of the components for the computed variational probability. A gating function optimization unit 84 optimizes a gating function model that is a model for determining a branch direction according to the multivariate data in a node of the hierarchical latent structure, based on the variational probability of the latent variable in the node.

    Abstract translation: 分层潜在结构设置单元81设置作为其中潜变量由树结构表示的结构的分层潜在结构，并且表示概率模型的分量位于树结构的最底层的节点处。 变分概率计算单元82计算作为潜在变量的路径潜变量的变分概率，所述潜变量包括在将根节点链接到分层潜在结构中的目标节点的路径中。 分量优化单元83针对所计算的变分概率优化每个分量。 门控功能优化单元84基于节点中的潜在变量的变分概率来优化门控功能模型，门控功能模型是根据层级潜在结构的节点中的多变量数据确定分支方向的模型。

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