Enhanced model updating using vector space transformations for model mapping
US11676049B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 13, 2020 |
| Grant date | Jun 13, 2023 |
| Priority date | — |
| Expiry date | Oct 16, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/022
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems and methods for updating static machine-learning models (e.g., a Doc2Vec model) without needing to retrain the models. More particularly, the present disclosure relates to systems and methods that can be used to add new data to a base model by training a client model using the new data, and transforming the vector space of the client model to align with the vector space of the base model. The base model can then be updated using the realigned client model. As such, the base model can be updated with the new data without needing to retrain the base model, which can be burdensome to processing resources, insecure, and time consuming.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.