Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network.
Siqi LiangYan SunFaming LiangPublished in: CoRR (2022)
Keyphrases
- dimension reduction
- neural network
- manifold embedding
- feature extraction
- principal component analysis
- high dimensional
- high dimensional problems
- nonlinear manifold
- linear discriminant analysis
- data mining and machine learning
- random projections
- artificial neural networks
- cluster analysis
- low dimensional
- feature space
- partial least squares
- singular value decomposition
- high dimensionality
- high dimensional data
- preprocessing
- feature selection
- manifold learning
- high dimensional data analysis
- variable selection
- kernel pca
- discriminative information
- unsupervised learning
- self organizing maps
- high dimensional feature space
- dimensionality reduction
- discriminant analysis
- head pose estimation
- maximum likelihood
- intrinsic dimension
- association rules
- data mining