Dimensionality Reduction and Clustering on Statistical Manifolds.
Sang-Mook LeeA. Lynn AbbottPhilip A. AramanPublished in: CVPR (2007)
Keyphrases
- dimensionality reduction
- high dimensional data
- low dimensional
- manifold learning
- high dimensionality
- high dimensional
- clustering algorithm
- pattern recognition and machine learning
- clustering method
- data points
- nonlinear dimensionality reduction
- unsupervised learning
- information theoretic
- multidimensional scaling
- principal component analysis
- linear discriminant analysis
- principal components
- feature space
- unsupervised feature selection
- principal components analysis
- k means
- neighborhood preserving
- statistical models
- neural network
- arbitrary dimension
- document clustering
- data clustering
- nearest neighbor
- manifold structure
- low dimensional spaces
- locally linear embedding
- data representation
- pattern recognition
- cluster analysis
- lower dimensional
- input space
- fuzzy clustering
- hierarchical clustering
- euclidean distance
- self organizing maps
- statistical analysis
- data analysis
- feature selection