A semi-supervised approach for dimensionality reduction with distributional similarity.
Feng ZhengZhan SongLing ShaoRonald ChungKui JiaXinyu WuPublished in: Neurocomputing (2013)
Keyphrases
- dimensionality reduction
- semi supervised
- subspace learning
- semi supervised dimensionality reduction
- manifold learning
- label information
- graph embedding
- diffusion maps
- kernel learning
- metric learning
- semi supervised learning
- principal component analysis
- labeled data
- high dimensional data
- high dimensional
- unsupervised learning
- unlabeled data
- high dimensionality
- data representation
- low dimensional
- semi supervised clustering
- feature extraction
- pairwise constraints
- active learning
- pattern recognition
- nonlinear dimensionality reduction
- data points
- pairwise
- multi view
- co training
- semi supervised classification
- dimensionality reduction methods
- pattern recognition and machine learning
- random projections
- dimension reduction
- data sets
- linear discriminant analysis
- low rank
- principal components
- kernel pca
- singular value decomposition
- sparse representation
- supervised learning
- feature selection
- structure preserving
- machine learning
- linear dimensionality reduction
- label propagation
- image processing
- labeled examples
- computer vision