Nonlinear Dimensionality Reduction via Path-Based Isometric Mapping.
Amir NajafiAmir JoudakiEmad FatemizadehPublished in: CoRR (2013)
Keyphrases
- nonlinear dimensionality reduction
- manifold learning
- mapping function
- low dimensional
- laplacian eigenmaps
- dimensionality reduction
- high dimensional
- high dimensional data
- semi supervised
- maximum variance unfolding
- subspace learning
- feature extraction
- feature space
- locally linear embedding
- sparse representation
- dimensionality reduction methods
- dimension reduction
- principal component analysis
- euclidean space
- data sets
- input image
- data analysis
- low dimensional manifolds
- feature selection