Searching for the embedded manifolds in high-dimensional data, problems and unsolved questions.
Jeanny HéraultAnne Guérin-DuguéPierre VillemainPublished in: ESANN (2002)
Keyphrases
- high dimensional data
- high dimensionality
- low dimensional
- high dimensions
- dimensionality reduction
- high dimensional
- manifold learning
- nearest neighbor
- low dimensional manifolds
- small sample size
- data points
- regression problems
- subspace clustering
- data analysis
- nonlinear dimensionality reduction
- dimension reduction
- similarity search
- data sets
- high dimensional spaces
- subspace learning
- clustering high dimensional data
- input space
- neural network
- low rank
- original data
- data distribution
- input data
- computer vision
- higher dimensional
- linear discriminant analysis
- sparse representation
- data structure
- database