System and method for automatic hyperparameter selection for online learning
US12361331B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 4, 2021 |
| Grant date | Jul 15, 2025 |
| Priority date | — |
| Expiry date | Mar 25, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/105
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for tuning hyperparameters for a machine learning model using a challenger champion model are described. A set of challenger configurations are generated based on a hyperparameter for tuning and a subset of the set of challenger configurations are scheduled for evaluation based on a loss function. A loss value derived from the loss function for the challenger configurations is compared to a loss value derived from the loss function for a champion configuration, and the champion configuration is replaced with the challenger configuration based on the comparison of the loss value derived from the loss function for the challenger configuration and the loss value derived from the loss function for the champion configuration. When the champion is replaced, a new set of challenger configurations is generated based on the new champion configuration.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.