Minimum Similarity Sampling Scheme for Nyström Based Spectral Clustering on Large Scale High-Dimensional Data.
Zhicheng ZengMing ZhuHong YuHonglian MaPublished in: IEA/AIE (2) (2014)
Keyphrases
- spectral clustering
- high dimensional data
- similarity matrix
- normalized cut
- clustering method
- subspace clustering
- nearest neighbor
- low dimensional
- dimensionality reduction
- high dimensional
- data clustering
- high dimensionality
- pairwise
- clustering quality
- similarity measure
- data sets
- data points
- eigendecomposition
- low rank matrix approximation
- data analysis
- input space
- clustering algorithm
- similarity search
- dimension reduction
- linear discriminant analysis
- k means
- high dimensional spaces
- distance function
- sparse representation
- euclidean distance
- low rank
- image segmentation
- manifold learning
- low rank approximation
- graph laplacian
- real world
- graph partitioning
- distance measure
- binary codes
- knowledge discovery
- pattern recognition
- image processing
- machine learning
- edit distance
- input data
- unsupervised learning