Locally multidimensional scaling by creating neighborhoods in diffusion maps.
Tomer LancewickiMayer AladjemPublished in: Neurocomputing (2014)
Keyphrases
- multidimensional scaling
- diffusion maps
- dimensionality reduction
- low dimensional
- manifold learning
- nonlinear dimensionality reduction
- high dimensional
- principal component analysis
- high dimensional data
- euclidean distance
- semi supervised
- dimension reduction
- pattern recognition
- geodesic distance
- feature extraction
- kernel pca
- data points
- feature space
- input space
- vector space
- euclidean space
- sparse representation
- cluster analysis
- data sets
- neural network
- singular value decomposition
- active learning
- machine learning