Divergence based graph estimation for manifold learning.
Karim T. Abou-MoustafaFrank P. FerrieDale SchuurmansPublished in: GlobalSIP (2013)
Keyphrases
- manifold learning
- neighborhood graph
- low dimensional
- dimensionality reduction
- diffusion maps
- high dimensional
- semi supervised
- nonlinear dimensionality reduction
- dimension reduction
- subspace learning
- high dimensional data
- laplacian eigenmaps
- head pose estimation
- feature extraction
- manifold structure
- intrinsic dimensionality
- computer vision
- graph construction
- latent space
- locally linear embedding
- sparse representation
- graph laplacian
- weighted graph
- density estimation
- riemannian manifolds
- nonlinear manifold
- manifold learning algorithm
- graph embedding
- neural network
- discriminant embedding
- manifold embedding
- feature selection
- image processing
- principal component analysis
- random walk