Encoding machine-learning models and determining ownership of machine-learning models
US11521121B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Sep 12, 2019 |
| Grant date | Dec 6, 2022 |
| Priority date | — |
| Expiry date | Jun 17, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L25/30
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and non-transitory computer readable storage media are disclosed for generating a machine-learning model and encoding ownership information in the machine-learning model. For example, the disclosed system can generate parameters of a machine-learning model utilizing digital content items modified by a filter. The disclosed system can then process digital content items modified by the filter to generate first outputs based on the digital content items being modified by the filter. The disclosed system can also process digital content items unmodified by the filter to generate second outputs based on the digital content items not being modified by the filter. The disclosed system can determine that the second outputs are degraded relative to the first outputs. Accordingly, the disclosed system can determine ownership of the machine-learning model based on detecting that information about the filter is embedded in parameters of the machine-learning model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.