Semi-supervised learning with mixed-order graph convolutional networks

•We propose a novel end-to-end model for graph-based semi-supervised learning.•The high-order connectivity among nodes can be obtained by GCN learners.•Unlabeled nodes are utilized to augment the diversity among the GCN learners.•Show the effectiveness of the proposed model.