Kernel K-Means Low Rank Approximation for Spectral Clustering and Diffusion Maps.
Carlos M. AlaízÁngela FernándezYvonne GalaJosé R. DorronsoroPublished in: IDEAL (2014)
Keyphrases
- spectral clustering
- low rank approximation
- k means
- normalized cut
- clustering method
- data clustering
- clustering algorithm
- eigendecomposition
- pairwise
- nonnegative matrix factorization
- similarity matrix
- graph partitioning
- manifold learning
- kernel methods
- kernel matrix
- cluster analysis
- support vector
- computer vision
- reproducing kernel hilbert space
- image segmentation
- feature space
- multiple kernel learning
- data sets
- negative matrix factorization
- machine learning