Patent · US Active

Compressed recurrent neural network models

US10878319B2 · kind B2 · utility

2Cited by
2References
15Claims
0Family size

Assignee

Inventors

Key dates

Filing dateDec 29, 2016
Grant dateDec 29, 2020
Priority date
Expiry dateAug 6, 2039

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06N3/084
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for implementing a compressed recurrent neural network (RNN). One of the systems includes a compressed RNN, the compressed RNN comprising a plurality of recurrent layers, wherein each of the recurrent layers has a respective recurrent weight matrix and a respective inter-layer weight matrix, and wherein at least one of recurrent layers is compressed such that a respective recurrent weight matrix of the compressed layer is defined by a first compressed weight matrix and a projection matrix and a respective inter-layer weight matrix of the compressed layer is defined by a second compressed weight matrix and the projection matrix.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.