Kernel Principal Components Are Maximum Entropy Projections.
António R. C. PaivaJian-Wu XuJosé Carlos PríncipePublished in: ICA (2006)
Keyphrases
- maximum entropy
- principal components
- kernel space
- kernel principal component analysis
- principal component regression
- maximum entropy principle
- principal component analysis
- dimensionality reduction
- kernel function
- conditional random fields
- hyperplane
- principle of maximum entropy
- feature space
- kernel pca
- transformation based learning
- iterative scaling
- kernel logistic regression
- minimum cross entropy
- kernel matrix
- kernel methods
- covariance matrix
- partial least squares
- kernel machines
- feature set
- higher order
- pattern recognition
- support vector
- bayesian networks
- face recognition
- computer vision