Graph learning in low dimensional space for graph convolutional networks.
Beixian ZhangMeiling LiuBo ZhouXingyi LiuPublished in: Multim. Tools Appl. (2022)
Keyphrases
- low dimensional
- high dimensional
- graph structure
- learning process
- learning algorithm
- fully connected
- graph embedding
- graph theory
- graph representation
- random walk
- equivalence classes
- connectionist networks
- complex networks
- structured data
- unsupervised learning
- active learning
- average degree
- deep learning
- network analysis
- graph layout
- small world
- edge weights
- graph model
- graph mining
- community detection
- input space
- graph matching
- reinforcement learning