Training of artificial neural networks using safe mutations based on output gradients
US10699195B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 14, 2018 |
| Grant date | Jun 30, 2020 |
| Priority date | — |
| Expiry date | Dec 14, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/098
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are disclosed herein for ensuring a safe mutation of a neural network. A processor determines a threshold value representing a limit on an amount of divergence of response for the neural network. The processor identifies a set of weights for the neural network, the set of weights beginning as an initial set of weights. The processor trains the neural network by repeating steps including determining a safe mutation representing a perturbation that results in a response of the neural network that is within the threshold divergence, and modifying the set of weights of the neural network in accordance with the safe mutation.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.