Concurrent ensemble model training for open sets
US11636286B1 · kind B1 · utility
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20Claims
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Key dates
| Filing date | May 1, 2020 |
| Grant date | Apr 25, 2023 |
| Priority date | — |
| Expiry date | Jul 17, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/809
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Described are systems and methods for training machine learning models of an ensemble of models that are de-correlated. For example, two or more machine learning models may be concurrently trained (e.g., co-trained) while adding a decorrelation component to one or both models that decreases the pairwise correlation between the outputs of the models. Unlike traditional approaches, in accordance with the disclosed implementations, only the negative results need to be decorrelated.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.