Self-supervised graph convolutional clustering by preserving latent distribution.
Shiwen KouWei XiaXiangdong ZhangQuanxue GaoXinbo GaoPublished in: Neurocomputing (2021)
Keyphrases
- graph theoretic
- graph clustering
- graph partitioning
- graph model
- random walk
- directed graph
- graph representation
- clustering algorithm
- self organizing maps
- clustering method
- cluster analysis
- document clustering
- unsupervised learning
- graph construction
- spectral methods
- k means
- probability distribution
- similarity matrix
- graph structure
- graph theory
- latent variables
- bipartite graph
- structured data
- spectral clustering
- data clustering
- information theoretic
- data distribution
- hierarchical clustering
- partitioning algorithm
- spanning tree
- graph mining
- weighted graph
- graph matching
- dimensionality reduction
- high dimensional
- pairwise