Deeper insights into graph convolutional networks for semi-supervised learning

Keyphrases

• Semi-supervised Learning 100%
• Graph Convolutional Network 100%
• Network Model 40%
• Convolutional Layer 20%
• Machine Learning 10%
• State-of-the-art Techniques 10%
• Over-smoothing 10%
• Model Selection 10%
• Labeled Data 10%
• Graph Topology 10%
• Graph-based Semi-supervised Learning 10%
• Laplacian Smoothing 10%
• Training Approaches 10%
• Shallow Architectures 10%
• Self-training 10%
• Co-training 10%
• Deep Learning System 10%
• Vertex Feature 10%
• Few Labels 10%
• Fundamental Limits 10%

Computer Science

• Graph Convolutional Network 100%
• Semisupervised Learning 100%
• Convolutional Layer 22%
• Machine Learning 11%
• Considerable Amount 11%
• Topology Graph 11%
• Laplacian Smoothing 11%
• Deep Learning 11%
• Fundamental Limit 11%
• Graph Convolution 11%