Discriminative locality preserving dimensionality reduction based on must-link constraints.
Guosheng LiuMeizhu YangPublished in: EMEIT (2011)
Keyphrases
- locality preserving
- dimensionality reduction
- pairwise constraints
- semi supervised
- data representation
- manifold learning
- locality preserving projections
- kernel learning
- pairwise
- kernel trick
- metric learning
- discriminative learning
- spectral clustering
- low dimensional
- feature extraction
- principal component analysis
- high dimensional data
- high dimensional
- loss function
- input space
- pattern recognition
- dimensionality reduction methods
- latent semantic indexing
- face recognition
- data points
- feature selection
- linear discriminant analysis
- embedding space
- nonlinear dimensionality reduction
- euclidean distance
- unsupervised learning
- high dimensionality
- subspace learning
- feature space
- labeled data
- semi supervised learning
- document clustering
- unlabeled data
- decision boundary
- kernel pca
- hash functions
- knn
- locality sensitive hashing
- basis functions
- distance metric
- vector space
- dimension reduction