Dimensionality Reduction on Grassmannian via Riemannian Optimization: A Generalized Perspective.
Tianci LiuZelin ShiYunpeng LiuPublished in: CoRR (2017)
Keyphrases
- feature space
- dimensionality reduction
- subspace learning
- manifold learning
- high dimensionality
- low dimensional
- principal component analysis
- high dimensional
- feature selection
- data representation
- global optimization
- high dimensional data
- riemannian manifolds
- linear discriminant analysis
- optimization algorithm
- graph embedding
- principal components
- nonlinear dimensionality reduction
- dimensionality reduction methods
- euclidean space
- optimization problems
- nearest neighbor
- finite dimensional
- optimization method
- vector space
- affine invariant
- data sets
- discriminant analysis