Automatically scalable system for serverless hyperparameter tuning
US11256555B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 26, 2018 |
| Grant date | Feb 22, 2022 |
| Priority date | — |
| Expiry date | Dec 12, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A scalable system and method for completing a model task using a serverless architecture is disclosed. The system may include a model optimizer having one or more memory units for storing instructions and one or more processors. The method may include receiving a request to complete a model task, and retrieving a stored model and a first hyperparameter based on the request. The method may include provisioning first computing resources to a development instance configured to train the retrieved model based on the first hyperparameter and the model task. The method may include receiving, from the development instance, a trained model and a performance metric. The method may include receiving, from a different development instance, a different performance metric associated with a different model, and terminating the development instance based on a determination that the termination condition is satisfied.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.