Incremental Manifold Learning Algorithm Using PCA on Overlapping Local Neighborhoods for Dimensionality Reduction.
Yubin ZhanJianping YinGuomin ZhangEn ZhuPublished in: ISICA (2008)
Keyphrases
- manifold learning algorithm
- dimensionality reduction
- manifold learning
- principal component analysis
- low dimensional
- high dimensional
- high dimensional data
- pattern recognition
- locally linear embedding
- data points
- data representation
- dimensionality reduction methods
- feature space
- high dimensionality
- feature extraction
- feature selection
- euclidean distance
- singular value decomposition
- linear discriminant analysis
- subspace learning
- random projections
- principal components
- unsupervised learning
- principal components analysis
- lower dimensional
- linear dimensionality reduction
- preprocessing step
- dimension reduction
- sparse representation
- nonlinear manifold
- locality preserving projections
- metric learning
- face images
- semi supervised
- computer vision
- learning algorithm
- machine learning