Kernel k-means
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have ...
Publications
2 shownWeighted Graph Cuts without Eigenvectors A Multilevel Approach
A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods....
Frequent Co-Authors
Researcher Info
- h-index
- 2
- Publications
- 2
- Citations
- 2,200
- Institution
- The University of Texas at Austin
External Links
Identifiers
- ORCID
- 0000-0002-1704-3838
Impact Metrics
h-index
2
h-index: Number of publications with at least h citations each.