A Closer Look at Embedding Propagation for Manifold Smoothing.
Diego A. VelázquezPau RodríguezJosep M. GonfausF. Xavier RocaJordi GonzalezPublished in: J. Mach. Learn. Res. (2022)
Keyphrases
- manifold embedding
- nonlinear dimensionality reduction
- graph embedding
- laplacian eigenmaps
- geodesic distance
- embedding space
- manifold learning
- head pose estimation
- euclidean space
- vector space
- heat kernel
- low dimensional
- dimensionality reduction
- smoothing algorithm
- locality preserving projections
- smoothing methods
- image smoothing
- euclidean distance
- wave propagation
- feature extraction
- tangent space
- semi supervised
- manifold structure
- kernel pca
- multi dimensional scaling
- propagation model
- pairwise distances
- latent space
- data sets
- multidimensional scaling
- preprocessing step
- dimension reduction
- principal component analysis
- high dimensional
- information retrieval