Nonlinear Dimensionality Reduction by Topologically Constrained Isometric Embedding.
Guy RosmanMichael M. BronsteinAlexander M. BronsteinRon KimmelPublished in: Int. J. Comput. Vis. (2010)
Keyphrases
- nonlinear dimensionality reduction
- manifold learning
- low dimensional
- laplacian eigenmaps
- maximum variance unfolding
- dimensionality reduction
- high dimensional data
- high dimensional
- locally linear embedding
- semi supervised
- feature mapping
- feature extraction
- dimension reduction
- subspace learning
- low dimensional manifolds
- euclidean space
- embedding space
- riemannian manifolds
- machine learning
- neural network
- feature selection
- dimensionality reduction methods
- feature space