A multi-label-based federated learning method, device and system

Abstract

The embodiment of this specification provides a multi-label-based federated learning method, device and system, the method includes: when multiple institutions are performing federated learning, the trusted execution environment can obtain multiple tag data sets provided by multiple institutions, Any tag data group includes the original tags of multiple users, and among the multiple users, there is at least one user whose multiple original tags in the multiple tag data groups are inconsistent; after obtaining multiple tag data groups, Using a preset weakly supervised learning algorithm to carry out learning and training on the plurality of label data sets to obtain a unified target label data set, the target label data set includes the target labels of the multiple users; the target label data set and sent to the multiple institutions, so that the multiple institutions can perform federated learning based on the target label data set.

Description

technical field [0001] This document relates to the field of federated learning, in particular to a multi-label-based federated learning method, device and system. Background technique [0002] Federated learning (also known as federated learning, federated learning) is a machine learning framework that can effectively help multiple organizations perform data usage and machine learning modeling while meeting user privacy protection and data security requirements. [0003] Usually, multiple institutions can perform learning and training based on sample label data and feature data when performing federated learning, where the sample label data can be provided by multiple institutions. However, due to the business scenarios of multiple institutions or different definitions of labels, the label data provided by multiple institutions are usually inconsistent. In this way, when performing federated learning, it will not be possible to determine which institution's label data shall...

AI Technical Summary

Problems solved by technology

[0004] The embodiment of this specification provides a multi-label-based federated learning method, device and system, which is used to solve the problem that in federated learning, when the label data provided by multiple institutions is inconsistent, it is impossible to determine which institution's label data is used for learning. training problem

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