Communication efficient machine learning of data across multiple sites
US11699080B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 14, 2018 |
| Grant date | Jul 11, 2023 |
| Priority date | — |
| Expiry date | Mar 9, 2042 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04Q9/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one embodiment, a service receives machine learning-based generative models from a plurality of distributed sites. Each generative model is trained locally at a site using unlabeled data observed at that site to generate synthetic unlabeled data that mimics the unlabeled data used to train the generative model. The service receives, from each of the distributed sites, a subset of labeled data observed at that site. The service uses the generative models to generate synthetic unlabeled data. The service trains a global machine learning-based model using the received subsets of labeled data received from the distributed sites and the synthetic unlabeled data generated by the generative models.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.