Neighborhood Smoothing Embedding for Noisy Manifold Learning.
Guisheng ChenJunsong YinDeyi LiPublished in: GrC (2008)
Keyphrases
- manifold learning
- nonlinear dimensionality reduction
- laplacian eigenmaps
- neighborhood graph
- manifold learning algorithm
- geodesic distance
- embedding space
- data embedding
- manifold embedding
- nonlinear manifold learning
- low dimensional
- locality preserving projections
- dimensionality reduction
- diffusion maps
- discriminant embedding
- semi supervised
- low dimensional manifolds
- high dimensional data
- high dimensional
- head pose estimation
- subspace learning
- locally linear embedding
- latent space
- feature extraction
- dimension reduction
- manifold structure
- locality preserving
- sparse representation
- graph embedding
- noisy data
- neural network
- vector space
- pattern recognition
- clustering method
- unsupervised learning
- feature space
- similarity measure
- feature selection