Compressed recurrent neural network models
US11948062B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 4, 2020 |
| Grant date | Apr 2, 2024 |
| Priority date | — |
| Expiry date | Mar 5, 2042 |
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.