Gradient-based kernel dimension reduction for supervised learning
Kenji FukumizuChenlei LengPublished in: CoRR (2011)
Keyphrases
- pairwise
- dimension reduction
- supervised learning
- unsupervised learning
- semi supervised
- feature space
- principle component analysis
- principal component analysis
- feature extraction
- high dimensional problems
- high dimensional
- partial least squares
- kernel function
- semi supervised learning
- random projections
- manifold learning
- low dimensional
- discriminative information
- learning tasks
- singular value decomposition
- cluster analysis
- variable selection
- support vector
- labeled data
- training samples
- kernel learning
- training data
- kernel methods
- feature selection
- dimension reduction methods
- dimensionality reduction
- class labels
- high dimensional data
- reinforcement learning
- training set
- high dimensional data analysis
- learning algorithm
- kernel matrix
- machine learning
- learning problems
- active learning
- linear discriminant analysis
- clustering method
- text classification