An iterated graph laplacian approach for ranking on manifolds.
Xueyuan ZhouMikhail BelkinNathan SrebroPublished in: KDD (2011)
Keyphrases
- graph laplacian
- euclidean space
- laplacian eigenmaps
- manifold structure
- underlying manifold
- random walk
- manifold learning
- spectral analysis
- spectral clustering
- pointwise
- basis functions
- low dimensional
- sparse coding
- weighted graph
- data points
- semi supervised learning
- neighborhood graph
- geometric structure
- kernel machines
- riemannian manifolds
- euclidean distance
- geodesic distance
- low rank
- shape analysis
- shape variations
- state space
- vector space
- feature space