Cooperative execution of a genetic algorithm with an efficient training algorithm for data-driven model creation
US9785886B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 17, 2017 |
| Grant date | Oct 10, 2017 |
| Priority date | — |
| Expiry date | Apr 17, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/0985
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method includes, based on a fitness function, selecting a subset of models from a plurality of models. The plurality of models is generated based on a genetic algorithm and corresponds to a first epoch of the genetic algorithm. Each of the plurality of models includes data representative of a neural network. The method also includes performing at least one genetic operation of the genetic algorithm with respect to at least one model of the subset to generate a trainable model and sending the trainable model to an optimization trainer. The method includes adding a trained model received from the optimization trainer as input to a second epoch of the genetic algorithm that is subsequent to the first epoch.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.