Manifold learning with iterative dimensionality photo-projection.
Daniel LückeheStefan OehmckeOliver KramerPublished in: IJCNN (2017)
Keyphrases
- manifold learning
- dimensionality reduction
- high dimensional
- discriminant projection
- intrinsic manifold
- low dimensional
- feature space
- nonlinear dimensionality reduction
- diffusion maps
- laplacian eigenmaps
- high dimensional data
- feature extraction
- high dimensionality
- subspace learning
- semi supervised
- data points
- high dimensional spaces
- dimension reduction
- head pose estimation
- intrinsic dimensionality
- manifold learning algorithm
- nonlinear manifold
- lower dimensional
- pattern recognition
- sparse representation
- principal component analysis
- input space
- dimensionality reduction methods
- manifold structure
- linear discriminant analysis
- locality preserving
- machine learning
- geodesic distance
- dimensional data
- singular value decomposition
- kernel function
- support vector machine
- image processing
- discriminant embedding