Fast Compressive Spectral Clustering for Large-Scale Sparse Graph.
Ting LiYiming ZhangHao LiuGuangtao XueLing LiuPublished in: IEEE Trans. Big Data (2022)
Keyphrases
- spectral clustering
- graph laplacian
- graph partitioning
- graph construction
- compressive sensing
- normalized cut
- laplacian matrix
- similarity matrix
- graph clustering
- label propagation
- spectral methods
- data clustering
- similarity graph
- clustering method
- low rank approximation
- eigenvalue decomposition
- pairwise
- sparse representation
- affinity matrix
- image segmentation
- clustering algorithm
- random projections
- random walk
- eigendecomposition
- low rank representation
- adjacency matrix
- constrained spectral clustering
- high dimensional
- k means
- nonnegative matrix factorization
- negative matrix factorization
- evolutionary clustering
- graph representation
- graph structure
- data mining
- low dimensional
- graph matching
- graph kernels
- cluster analysis
- model selection
- constrained clustering
- supervised learning
- heat kernel
- graph structures
- neighborhood graph
- similarity measure
- machine learning
- pairwise constraints