Spectral Sparse Representation for Clustering: Evolved from PCA, K-means, Laplacian Eigenmap, and Ratio Cut.
Zhenfang HuGang PanYueming WangZhaohui WuPublished in: CoRR (2014)
Keyphrases
- k means
- sparse representation
- laplacian eigenmaps
- manifold learning
- kernel pca
- face recognition
- clustering algorithm
- dimensionality reduction
- spectral clustering
- sparse coding
- data clustering
- clustering method
- random projections
- negative matrix factorization
- principal component analysis
- signal processing
- high dimensional data
- cluster analysis
- image classification
- image patches
- image representation
- principal components analysis
- subspace learning
- expectation maximization
- locally linear embedding
- feature extraction
- natural images
- linear discriminant analysis
- neural network
- input space
- similarity measure
- document clustering
- data points
- unsupervised learning
- low dimensional
- face images