Sufficient Dimension Reduction via Direct Estimation of the Gradients of Logarithmic Conditional Densities.
Hiroaki SasakiVoot TangkarattMasashi SugiyamaPublished in: ACML (2015)
Keyphrases
- dimension reduction
- high dimensional
- feature extraction
- principal component analysis
- low dimensional
- probability density
- linear discriminant analysis
- data mining and machine learning
- high dimensional problems
- variable selection
- partial least squares
- manifold learning
- feature selection
- singular value decomposition
- high dimensional data
- random projections
- high dimensionality
- cluster analysis
- unsupervised learning
- dimensionality reduction
- intrinsic dimensionality
- density estimation
- feature space
- discriminative information
- pattern recognition
- high dimensional data analysis
- probability density function
- neural network
- preprocessing
- intrinsic dimension
- manifold embedding