Systems and methods for learning user representations for open vocabulary data sets
US11568315B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 21, 2020 |
| Grant date | Jan 31, 2023 |
| Priority date | — |
| Expiry date | Jul 10, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods adapted for training a machine learning model to predict data labels are described. The approach includes receiving a first data set comprising first data objects and associated first data labels, and processing, with a user representation model, respective first data objects and associated data labels associated with a unique user representation by fusing the respective first data object and the associated first data labels. First data object representations of the respective first data objects are generated, and the first data object representations and the user representation model outputs are fused to create a user conditional object representation. The machine learning model updates corresponding parameters based on an error value based on a maximum similarity of the projections of the respective user conditional object representation and first data labels in a joint embedding space.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.