Method, apparatus and system for secure vertical federated learning
US11836583B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 8, 2020 |
| Grant date | Dec 5, 2023 |
| Priority date | — |
| Expiry date | Aug 1, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q30/0201
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A machine learning model is learned using secure vertical federated learning by receiving, by a network machine learning model, from a plurality of private machine learning models, a set of private machine learning model outputs. The set of private machine learning model outputs is based on data owned exclusively by each of the plurality of private machine learning models. The set of private machine learning model machine learning outputs is aligned based on sample IDs of the data. The network machine learning model, a prediction, the prediction being the output of the network model based on the set of private machine learning model outputs. Transmitting, by the network model, the prediction, to one of the plurality of private machine learning models, the one of the plurality of private machine learning models comprising labels. Receiving, by the network model, from the one of the plurality of private machine learning models, a loss based on the labels and the prediction, and calculating a gradient based on the loss, and updating a parameter of the network model based on the loss.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.