Concurrent optimization of machine learning model performance
US12182676B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 13, 2023 |
| Grant date | Dec 31, 2024 |
| Priority date | — |
| Expiry date | Dec 13, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/088
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Certain aspects of the present disclosure provide techniques for concurrently performing inferences using a machine learning model and optimizing parameters used in executing the machine learning model. An example method generally includes receiving a request to perform inferences on a data set using the machine learning model and performance metric targets for performance of the inferences. At least a first inference is performed on the data set using the machine learning model to meet a latency specified for generation of the first inference from receipt of the request. While performing the at least the first inference, operational parameters resulting in inference performance approaching the performance metric targets are identified based on the machine learning model and operational properties of the computing device. The identified operational parameters are applied to performance of subsequent inferences using the machine learning model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.