Shenglin Zhao

Improving Your Graph Neural Networks: A High-Frequency Booster

2022 · arXiv (Cornell University)

Graph neural networks (GNNs) hold the promise of learning efficient representations of graph-structured data, and one of its most important applications is semi-supervised node classification. However, in this application, GNN frameworks tend to fail due …

STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems

2019 · arXiv (Cornell University)

We propose a new STAcked and Reconstructed Graph Convolutional Networks (STAR-GCN) architecture to learn node representations for boosting the performance in recommender systems, especially in the cold start scenario. STAR-GCN employs a stack of GCN …