Accurate and interpretable classification with hard attention
US11475277B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 13, 2020 |
| Grant date | Oct 18, 2022 |
| Priority date | — |
| Expiry date | Jan 6, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/70
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Generally, the present disclosure is directed to novel machine-learned classification models that operate with hard attention to make discrete attention actions. The present disclosure also provides a self-supervised pre-training procedure that initializes the model to a state with more frequent rewards. Given only the ground truth classification labels for a set of training inputs (e.g., images), the proposed models are able to learn a policy over discrete attention locations that identifies certain portions of the input (e.g., patches of the images) that are relevant to the classification. In such fashion, the models are able to provide high accuracy classifications while also providing an explicit and interpretable basis for the decision.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.