Laplacian Matrix for Dimensionality Reduction and Clustering.
Laurenz WiskottFabian SchönfeldPublished in: CoRR (2019)
Keyphrases
- dimensionality reduction
- laplacian matrix
- low dimensional
- spectral methods
- spectral clustering
- high dimensional data
- high dimensionality
- manifold learning
- data points
- unsupervised learning
- clustering algorithm
- clustering method
- data clustering
- k means
- principal component analysis
- feature extraction
- document clustering
- high dimensional
- spectral analysis
- graph partitioning
- cluster analysis
- distance metric
- euclidean distance
- kernel pca
- nonlinear dimensionality reduction
- heat kernel
- graph construction
- graph kernels
- feature selection
- pattern recognition
- geodesic distance
- data representation
- euclidean space
- feature space
- dimension reduction
- sparse representation
- semi supervised