Representation Learning Using Multi-Task Deep Neural Networks
    1.
    发明申请
    Representation Learning Using Multi-Task Deep Neural Networks 审中-公开
    使用多任务深层神经网络的表征学习

    公开(公告)号:US20170032035A1

    公开(公告)日:2017-02-02

    申请号:US14811808

    申请日:2015-07-28

    CPC classification number: G06N3/08 G06F17/3069 G06F17/30867

    Abstract: A system may comprise one or more processors and memory storing instructions that, when executed by one or more processors, configure one or more processors to perform a number of operations or tasks, such as receiving a query or a document, and mapping the query or the document into a lower dimensional representation by performing at least one operational layer that shares at least two disparate tasks.

    Abstract translation: 系统可以包括一个或多个处理器和存储器存储指令,当由一个或多个处理器执行时,配置一个或多个处理器来执行多个操作或任务,诸如接收查询或文档,以及映射查询或 通过执行共享至少两个不同任务的至少一个操作层来将文档转换成较低维度的表示。

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