Generating sets of training programs for machine learning models
US10949741B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 23, 2017 |
| Grant date | Mar 16, 2021 |
| Priority date | — |
| Expiry date | Nov 28, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/3346
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method, system and computer program product for generating sets of training programs for machine learning models. Fixed values of one or more workload metrics are received from a user, where the workload metrics correspond to low-level program features which define particular low-level application behavior. A profile using the fixed values of the workload metrics is then created. A suite of synthetic applications is generated using the created profile to form a set of training programs which target particular aspects of program behavior. A machine learning model is then trained using the set of training programs. Since the generated synthetic applications provide a broader coverage of the program state-space, the formed set of training programs more accurately targets performance behavior thereby improving the prediction accuracy of the machine learning based predictive models.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.