Semi-supervised Dimension Reduction with Kernel Sliced Inverse Regression.
Chiao-Ching HuangKuan-Ying SuPublished in: TAAI (2014)
Keyphrases
- dimension reduction
- semi supervised
- partial least squares
- regression algorithm
- manifold regularization
- unsupervised learning
- kernel trick
- feature space
- reproducing kernel hilbert space
- principal component analysis
- manifold learning
- semi supervised learning
- support vector
- kernel learning
- high dimensional
- high dimensional data
- singular value decomposition
- random projections
- kernel function
- dimensionality reduction
- regression model
- variable selection
- labeled data
- linear discriminant analysis
- high dimensional problems
- low dimensional
- feature extraction
- subspace learning
- unlabeled data
- active learning
- supervised learning
- kernel methods
- metric learning
- cluster analysis
- multiple kernel learning
- feature selection
- pairwise
- object recognition
- high dimensionality
- loss function
- pairwise constraints
- image processing
- low rank
- model selection
- decision trees
- data sets