Invertible Manifold Learning for Dimension Reduction.
Siyuan LiHaitao LinZelin ZangLirong WuJun XiaStan Z. LiPublished in: ECML/PKDD (3) (2021)
Keyphrases
- dimension reduction
- manifold learning
- low dimensional
- feature extraction
- diffusion maps
- high dimensional
- nonlinear dimensionality reduction
- principal component analysis
- high dimensional data
- subspace learning
- singular value decomposition
- feature selection
- feature space
- dimensionality reduction
- discriminative information
- linear discriminant analysis
- manifold learning algorithm
- cluster analysis
- random projections
- high dimensionality
- head pose estimation
- locally linear embedding
- unsupervised learning
- manifold structure
- manifold embedding
- computer vision
- preprocessing
- principle component analysis
- neural network
- k nearest neighbor
- riemannian manifolds
- nearest neighbor
- discriminant analysis
- low dimensional manifolds
- training data