RKHS Bayes Discriminant: A Subspace Constrained Nonlinear Feature Projection for Signal Detection.
Umut OzertemDeniz ErdogmusPublished in: IEEE Trans. Neural Networks (2009)
Keyphrases
- signal detection
- locality preserving projections
- discriminant subspace
- discriminant analysis
- principal component analysis
- kernel based nonlinear
- low dimensional
- linear dimensionality reduction
- kernel pca
- kernel methods
- face recognition
- subspace analysis
- random projections
- subspace learning
- feature vectors
- feature extraction
- dimensionality reduction
- null space
- decision trees
- feature set
- linear projection
- high dimensional
- support vector machine
- low signal to noise ratio
- linear subspace
- subspace clustering
- nearest feature line
- manifold learning
- feature space
- training data
- loss function
- high dimensional data