Research Article
Link Prediction and Node Classification Based on Multitask Graph Autoencoder
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 |
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