Multi-task machine learning architectures and training procedures
US12008459B2 · kind B2 · utility
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Key dates
| Filing date | Jun 17, 2019 |
| Grant date | Jun 11, 2024 |
| Priority date | — |
| Expiry date | Apr 7, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/048
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
This document relates to architectures and training procedures for multi-task machine learning models, such as neural networks. One example method involves providing a multi-task machine learning model having one or more shared layers and two or more task-specific layers. The method can also involve performing a pretraining stage on the one or more shared layers using one or more unsupervised prediction tasks. The method can also involve performing a tuning stage on the one or more shared layers and the two or more task-specific layers using respective task-specific objectives.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.