Non-redundant Spectral Dimensionality Reduction.
Yochai BlauTomer MichaeliPublished in: ECML/PKDD (1) (2017)
Keyphrases
- dimensionality reduction
- high dimensional data
- low dimensional
- high dimensionality
- dimensionality reduction methods
- principal component analysis
- data representation
- linear discriminant analysis
- high dimensional
- feature extraction
- highly redundant
- feature space
- pattern recognition
- spectral analysis
- hyperspectral imagery
- structure preserving
- lower dimensional
- nonlinear dimensionality reduction
- computer vision
- input space
- pattern recognition and machine learning
- principal components
- eliminate redundant
- manifold learning
- linear projection
- spectral images
- hyperspectral
- introducing additional
- embedding space
- data points
- euclidean distance
- dimension reduction
- random projections
- semi supervised
- graph embedding
- spatial frequency
- spectral features
- data analysis
- redundant data
- linear dimensionality reduction
- neural network
- normalized cut
- hyperspectral images