Semi-supervised sufficient dimension reduction under class-prior change.
Hideko KawakuboMasashi SugiyamaPublished in: TAAI (2016)
Keyphrases
- dimension reduction
- semi supervised
- principal component analysis
- manifold learning
- manifold regularization
- singular value decomposition
- high dimensional
- feature extraction
- high dimensional problems
- unsupervised learning
- low dimensional
- random projections
- dimensionality reduction
- high dimensionality
- discriminative information
- feature selection
- partial least squares
- high dimensional data
- semi supervised learning
- feature space
- linear discriminant analysis
- dimension reduction methods
- generative topographic mapping
- supervised learning
- subspace learning
- scatter matrices
- unlabeled data
- neural network
- manifold embedding
- sparse metric learning
- data sets
- null space
- metric learning
- cluster analysis
- pattern recognition
- machine learning