Conditional random field model compression
US10140581B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 22, 2014 |
| Grant date | Nov 27, 2018 |
| Priority date | — |
| Expiry date | Dec 7, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Features are disclosed for generating models, such as conditional random field (“CRF”) models, that consume less storage space and/or transmission bandwidth than conventional models. In some embodiments, the generated CRF models are composed of fewer or alternate components in comparison with conventional CRF models. For example, a system generating such CRF models may forgo the use of large dictionaries or other cross-reference lists that map information extracted from input (e.g., “features”) to model parameters; reduce in weight (or exclude altogether) certain model parameters that may not have a significant effect on model accuracy; and/or reduce the numerical precision of model parameters.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.