To address the issue, we propose a multi-task matrix factorized graph neural network (MT-MF-GCN), which consists of two major components: (1) a GCN (graph convolutional network) basic module that ...

Second, we construct a dynamic graph matrix learning model, rather than using the heat kernel function to obtain a fixed graph matrix, to capture the discriminative information and the local manifold ...