As the study of graph neural networks becomes more intensive and
compreh...
Heterogeneous graph neural networks (GNNs) have been successful in handl...
Many real-world data can be modeled as heterogeneous graphs that contain...
Recent studies have shown that deep neural networks-based recommender sy...
Session-based recommendation is a challenging problem in the real-world
...
The industry and academia have proposed many distributed graph processin...
Feature engineering, a crucial step of machine learning, aims to extract...
Finding or monitoring subgraph instances that are isomorphic to a given
...
Bayesian optimization is a broadly applied methodology to optimize the
e...
Multi-modal information is essential to describe what has happened in a
...
Inspired by the fact that different modalities in videos carry complemen...
Local features at neighboring spatial positions in feature maps have hig...
Human action recognition from well-segmented 3D skeleton data has been
i...