Geometric Laplacian Eigenmap Embedding.
Leo TorresKevin S. ChanTina Eliassi-RadPublished in: CoRR (2019)
Keyphrases
- laplacian eigenmaps
- manifold learning
- nonlinear dimensionality reduction
- kernel pca
- dimensionality reduction
- maximum variance unfolding
- graph laplacian
- empirical mode decomposition
- locally linear embedding
- low dimensional
- dynamic time warping
- geometric structure
- subspace learning
- euclidean space
- dimensionality reduction methods
- input space
- pattern recognition
- support vector regression
- feature extraction
- neighborhood graph
- high dimensional data
- random walk
- wavelet transform
- high dimensional