Trace Ratio Optimization-Based Semi-Supervised Nonlinear Dimensionality Reduction for Marginal Manifold Visualization.
Zhao ZhangTommy W. S. ChowMing-Bo ZhaoPublished in: IEEE Trans. Knowl. Data Eng. (2013)
Keyphrases
- nonlinear dimensionality reduction
- manifold learning
- semi supervised
- diffusion maps
- laplacian eigenmaps
- dimensionality reduction
- subspace learning
- low dimensional
- locally linear embedding
- semi supervised learning
- data visualization
- pairwise
- low dimensional manifolds
- manifold structure
- labeled data
- kernel machines
- multi view
- high dimensional data
- geodesic distance
- riemannian manifolds
- data analysis
- supervised learning
- dimension reduction
- dimensionality reduction methods
- unsupervised learning
- multi dimensional
- active learning
- high dimensional
- data sets
- underlying manifold
- sparse representation