Kernel relative transformation with applications to enhancing locally linear embedding.
Guihua WenLijun JiangJun WenPublished in: IJCNN (2008)
Keyphrases
- locally linear embedding
- laplacian eigenmaps
- orthogonal projection
- manifold learning
- nonlinear dimensionality reduction
- dimensionality reduction
- kernel pca
- low dimensional
- high dimensional
- high dimensional data
- kernel function
- kernel methods
- principal component analysis
- feature space
- subspace learning
- dimensional data
- support vector
- underlying manifold
- neural network
- principal components analysis
- data analysis
- learning algorithm
- machine learning