Scalable training with approximate incremental laplacian eigenmaps and PCA.
Eleni MantziouSymeon PapadopoulosYiannis KompatsiarisPublished in: ACM Multimedia (2013)
Keyphrases
- laplacian eigenmaps
- kernel pca
- principal component analysis
- dimensionality reduction
- manifold learning
- nonlinear dimensionality reduction
- graph laplacian
- principal components analysis
- kernel methods
- training set
- feature extraction
- input space
- principal components
- training examples
- euclidean space
- kernel function
- locally linear embedding
- pattern recognition
- linear discriminant analysis
- kernel matrix
- dynamic time warping
- spectral clustering
- learning algorithm
- low dimensional
- image classification
- high dimensional
- face recognition