Scalable manifold learning by uniform landmark sampling and constrained locally linear embedding.
Dehua PengZhipeng GuiWenzhang WeiHuayi WuPublished in: CoRR (2024)
Keyphrases
- manifold learning
- locally linear embedding
- nonlinear dimensionality reduction
- laplacian eigenmaps
- dimensionality reduction
- low dimensional
- manifold learning algorithm
- diffusion maps
- high dimensional
- feature mapping
- high dimensional data
- semi supervised
- dimension reduction
- subspace learning
- feature extraction
- sparse representation
- sample size
- manifold structure
- geodesic distance
- image processing
- riemannian manifolds