Semi-supervised local multi-manifold Isomap by linear embedding for feature extraction.
Yan ZhangZhao ZhangJie QinLi ZhangBing LiFanzhang LiPublished in: Pattern Recognit. (2018)
Keyphrases
- manifold learning
- semi supervised
- nonlinear dimensionality reduction
- laplacian eigenmaps
- feature extraction
- manifold learning algorithm
- embedding space
- dimensionality reduction
- semi supervised learning
- low dimensional
- subspace learning
- locally linear embedding
- geodesic distance
- manifold embedding
- feature mapping
- graph embedding
- maximum variance unfolding
- manifold structure
- locality preserving projections
- manifold regularization
- labeled data
- dimension reduction
- pairwise
- low dimensional manifolds
- unlabeled data
- unsupervised learning
- latent space
- high dimensional
- semi supervised classification
- underlying manifold
- high dimensional data
- neighborhood graph
- low rank
- pairwise constraints
- linear subspace
- nonlinear dimension reduction
- multidimensional scaling
- label information
- active learning
- feature space
- semi supervised clustering
- sparse representation
- grassmann manifold
- image processing
- riemannian manifolds
- feature selection
- linear discriminant analysis
- supervised learning
- pattern recognition