Methods and systems for mining minority-class data samples for training a neural network
US11816183B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 11, 2020 |
| Grant date | Nov 14, 2023 |
| Priority date | — |
| Expiry date | Dec 21, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and systems for mining minority-class data samples are described. A minority-class mining service receives activations generated by an inner-layer of a client neural network that has been trained to perform a prediction task that involves classification. The minority-class mining service generates a recalibrated activation using a recalibration neural network, and generates an anomaly detector output using an anomaly detector. From the anomaly detector output, a minority-class score is computed for the data sample represented by a received activation. The computed minority-class score is compared against a minority-class threshold to identify a candidate minority-class data sample. The candidate minority-class data sample can then be labeled and added to the training dataset for the client neural network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.