Privacy-preserving graphical model training methods, apparatuses, and devices

Abstract

Some embodiments of this specification disclose graphical model training methods, apparatuses, and devices. In an embodiment, a method performed by a terminal device includes: acquiring node information of a first graph to be constructed, node information of a second graph and node connection information of the second graph, acquiring a latent vector of a first node that has training label information in the first graph, acquiring latent vectors of the second node and the node in the second graph. performing, based on the first sample data and the second sample data, model training on a graphical model sent by a server, acquiring gradient information corresponding to the trained graphical model, and sending the gradient information to the server for the server to update model parameters in the graphical model based on gradient information provided by different terminal devices to obtain an updated graphical model.