Invention Grant
- Patent Title: On-device neural networks for natural language understanding
-
Application No.: US16135545Application Date: 2018-09-19
-
Publication No.: US10885277B2Publication Date: 2021-01-05
- Inventor: Sujith Ravi , Zornitsa Kozareva
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Dority & Manning, P.A.
- Main IPC: G06F40/30
- IPC: G06F40/30 ; G06N3/08 ; G06N3/04 ; G06F40/253

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.
Public/Granted literature
- US20200042596A1 On-Device Neural Networks for Natural Language Understanding Public/Granted day:2020-02-06
Information query