Hypersurface Fitting via Jacobian Nonlinear PCA on Riemannian Space.
Jun FujikiShotaro AkahoPublished in: CAIP (1) (2011)
Keyphrases
- principal component analysis
- low dimensional
- kernel pca
- dimensionality reduction
- finite dimensional
- lower dimensional
- higher dimensional
- feature extraction
- jacobian matrix
- riemannian manifolds
- principal components analysis
- high dimensional
- euclidean space
- geodesic distance
- singular value decomposition
- vector space
- face recognition
- input space
- prediction error
- model fitting
- manifold learning
- principal components
- search space
- infinite dimensional