Techniques for adaptive pipelining composition for machine learning (ML)
US12118474B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 10, 2023 |
| Grant date | Oct 15, 2024 |
| Priority date | — |
| Expiry date | Apr 10, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L9/3247
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems and methods for an adaptive pipelining composition service that can identify and incorporate one or more new models into the machine learning application. The machine learning application with the new model can be tested off-line with the results being compared with ground truth data. If the machine learning application with the new model outperforms the previously used model, the machine learning application can be upgraded and auto-promoted to production. One or more parameters may also be discovered. The new parameters may be incorporated into the existing model in an off-line mode. The machine learning application with the new parameters can be tested off-line and the results can be compared with previous results with existing parameters. If the new parameters outperform the existing parameters as compared with ground-truth data, the machine learning application can be auto-promoted to production.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.