Trusted neural network system
US11651227B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 19, 2018 |
| Grant date | May 16, 2023 |
| Priority date | — |
| Expiry date | Dec 12, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In general, the disclosure describes techniques for facilitating trust in neural networks using a trusted neural network system. For example, described herein are multi-headed, trusted neural network systems that can be trained to satisfy one or more constraints as part of the training process, where such constraints may take the form of one or more logical rules and cause the objective function of at least one the heads of the trusted neural network system to steer, during machine learning model training, the overall objective function for the system toward an optimal solution that satisfies the constraints. The constraints may be non-temporal, temporal, or a combination of non-temporal and temporal. The constraints may be directly compiled to a neural network or otherwise used to train the machine learning model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.