Research Article

Link Prediction and Node Classification Based on Multitask Graph Autoencoder

Algorithm 2

Multitask graph autoencoder.
Input: the network with adjacency matrix , node labels, the parameters
Output: network representation and updated parameter
1: Apply Adam optimizer and ReLU activation function
2: Construct the similarity matrix
3: 
4: Repeat
5:  Based on , apply Equation (1) to obtain and
6:  
7:  
8:  
9:  
10:  Use to backpropagate through the whole network to obtain the parameter
11: Until converge
12: Obtain the network representations