Privacy-preserving asynchronous federated learning for vertical partitioned data
US11429903B2 · kind B2 · utility
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Inventors
Key dates
| Filing date | Jun 24, 2020 |
| Grant date | Aug 30, 2022 |
| Priority date | — |
| Expiry date | Apr 7, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F17/16
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
System and method for training a federated learning model asynchronously. The system includes a coordinator, an active computing device and a passive computing device in communication with each other. The active computing device has a processor and a storage device storing computer executable code. The computer executable code is configured to: train the federated learning model in the active computing device using dimensions of an instance in the active computing device; and instruct the at least one passive computing device to train the federated learning model in the at least one passive computing device using dimensions of the instance in the at least one passive computing device. The training instances in the active and the at least one passive computing devices do not correspond to each other at the same training time.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.