Dimensionality-Reduction Using Connectionist Networks.
Eric SaundPublished in: IEEE Trans. Pattern Anal. Mach. Intell. (1989)
Keyphrases
- connectionist networks
- dimensionality reduction
- high dimensional data
- high dimensional
- pattern recognition
- principal component analysis
- high dimensionality
- feature space
- feature extraction
- dynamical systems
- input space
- dimensionality reduction methods
- data points
- low dimensional
- data representation
- manifold learning
- structure preserving
- feature selection
- pattern recognition and machine learning
- random projections
- linear discriminant analysis
- sparse representation
- linear projection
- principal components
- lower dimensional
- neural network
- nonlinear dimensionality reduction
- graph embedding
- monte carlo
- machine learning