Training neural networks using data augmentation policies
US11205099B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 27, 2020 |
| Grant date | Dec 21, 2021 |
| Priority date | — |
| Expiry date | Jun 13, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a machine learning model. One of the methods includes obtaining a training data set for training a machine learning model, the training data set comprising a plurality of training inputs; determining a plurality of data augmentation policies, wherein each data augmentation policy defines a procedure for processing a training input to generate a transformed training input; for each data augmentation policy, training the machine learning model using the data augmentation policy; determining, for each data augmentation policy, a quality measure of the machine learning model that has been trained using the data augmentation policy; and selecting a final data augmentation policy based using the quality measures of the machine learning models.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.