Adaptive Dimensionality Reduction for Local Principal Component Analysis.
Nico MigendaWolfram SchenckPublished in: ETFA (2020)
Keyphrases
- dimensionality reduction
- principal component analysis
- principal components
- linear discriminant analysis
- low dimensional
- high dimensional data
- feature extraction
- high dimensionality
- high dimensional
- dimensionality reduction methods
- dimension reduction
- subspace learning
- lower dimensional
- independent component analysis
- singular value decomposition
- random projections
- data representation
- manifold learning
- linear dimensionality reduction
- face recognition
- feature selection
- dimensional reduction
- linear projection
- discriminant analysis
- feature space
- pattern recognition
- kernel pca
- locally linear embedding
- input space
- face images
- principal components analysis
- structure preserving
- data points
- feature vectors
- case study
- neural network