Learning non-differentiable weights of neural networks using evolutionary strategies
US11676035B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 23, 2020 |
| Grant date | Jun 13, 2023 |
| Priority date | — |
| Expiry date | Dec 16, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/044
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network. The neural network has a plurality of differentiable weights and a plurality of non-differentiable weights. One of the methods includes determining trained values of the plurality of differentiable weights and the non-differentiable weights by repeatedly performing operations that include determining an update to the current values of the plurality of differentiable weights using a machine learning gradient-based training technique and determining, using an evolution strategies (ES) technique, an update to the current values of a plurality of distribution parameters.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.