Federated doubly stochastic kernel learning on vertical partitioned data
US11636400B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Jun 24, 2020 |
| Grant date | Apr 25, 2023 |
| Priority date | — |
| Expiry date | Jul 2, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
System and method for prediction using a machine learning model. 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: obtain parameters of the machine learning model; retrieve an instance from the local data; sample a random direction of the instance; compute a dot product of the random direction and the instance, and calculate a random feature; compute predicted values of the instance in the active and passive computing devices and summarize them to obtain a final predicted value; determine a model coefficient using the random feature, the final predicted value, and a target value of the instance; update the machine learning model using the model coefficient; and predict a value for a new instance.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.