Partitioning Well-Clustered Graphs with k-Means and Heat Kernel.
Richard PengHe SunLuca ZanettiPublished in: CoRR (2014)
Keyphrases
- heat kernel
- k means
- graph laplacian
- graph structure
- shape analysis
- spectral clustering
- shape descriptors
- graph partitioning
- minimum spanning tree
- graph clustering
- weight matrix
- laplace beltrami
- euclidean distance
- normalized cut
- geodesic distance
- shape matching
- nodes of a graph
- spanning tree
- scale space
- clustering algorithm
- clustering method
- data clustering
- random walk
- euclidean space
- distance matrix
- expectation maximization
- graphical models
- image segmentation
- dimensionality reduction
- multidimensional scaling
- graph model
- weighted graph
- vector space
- medical images
- adjacency matrix
- medical imaging
- semi supervised
- probabilistic model