On-device neural networks for natural language understanding

    公开(公告)号:US10885277B2

    公开(公告)日:2021-01-05

    申请号:US16135545

    申请日:2018-09-19

    Applicant: Google LLC

    Abstract: The present disclosure provides projection neural networks and example applications thereof. In particular, the present disclosure provides a number of different architectures for projection neural networks, including two example architectures which can be referred to as: Self-Governing Neural Networks (SGNNs) and Projection Sequence Networks (ProSeqoNets). Each projection neural network can include one or more projection layers that project an input into a different space. For example, each projection layer can use a set of projection functions to project the input into a bit-space, thereby greatly reducing the dimensionality of the input and enabling computation with lower resource usage. As such, the projection neural networks provided herein are highly useful for on-device inference in resource-constrained devices. For example, the provided SGNN and ProSeqoNet architectures are particularly beneficial for on-device inference such as, for example, solving natural language understanding tasks on-device.

    PROJECTION NEURAL NETWORKS
    32.
    发明申请

    公开(公告)号:US20200349450A1

    公开(公告)日:2020-11-05

    申请号:US16926908

    申请日:2020-07-13

    Applicant: Google LLC

    Inventor: Sujith Ravi

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for a projection neural network. In one aspect, a projection neural network is configured to receive a projection network input and to generate a projection network output from the projection network input. The projection neural network includes a sequence of one or more projection layers. Each projection layer has multiple projection layer parameters, and is configured to receive a layer input, apply multiple projection layer functions to the layer input, and generate a layer output by applying the projection layer parameters for the projection layer to the projection function outputs.

    Projection neural networks
    33.
    发明授权

    公开(公告)号:US10748066B2

    公开(公告)日:2020-08-18

    申请号:US15983441

    申请日:2018-05-18

    Applicant: Google LLC

    Inventor: Sujith Ravi

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for a projection neural network. In one aspect, a projection neural network is configured to receive a projection network input and to generate a projection network output from the projection network input. The projection neural network includes a sequence of one or more projection layers. Each projection layer has multiple projection layer parameters, and is configured to receive a layer input, apply multiple projection layer functions to the layer input, and generate a layer output by applying the projection layer parameters for the projection layer to the projection function outputs.

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