Techniques for machine learning model selection for domain generalization
US12406210B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 16, 2022 |
| Grant date | Sep 2, 2025 |
| Priority date | — |
| Expiry date | Apr 10, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/285
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computing device may perform training of a set of machine learning models on a first data set associated with a first domain. In some examples, the training may include, for each machine learning model of the set of machine learning models, inputting, as values for a set of parameters of the respective sets of parameters and for an iteration of a set of iterations, a moving average of the set of parameters calculated over a threshold number of previous iterations. The computing device may select a set of model states that are generated during the training of the plurality of machine learning models based on a validation performance of the set of model states performed during the training. The computing device may then generate an ensembled machine learning model by aggregating the set of machine learning models corresponding to the set of selected model states.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.