Improving Robustness of Gaussian Process-Based Inferential Control System Using Kernel Principle Component Analysis.
Ali AbusninaDaniel KudenkoRolf RothPublished in: ICMLA (2014)
Keyphrases
- gaussian process
- principle component analysis
- gaussian processes
- independent component analysis
- reproducing kernel hilbert space
- regression model
- dimension reduction
- semi supervised
- bayesian framework
- lower dimensional
- feature space
- svm classifier
- kernel pca
- model selection
- hyperparameters
- feature extraction
- principal component analysis
- face recognition
- random projections
- covariance matrix
- singular value decomposition
- latent variables
- closed form
- principal components
- high dimensional
- high dimensional feature space
- data mining
- high dimensional data
- low dimensional
- dimensionality reduction
- pairwise
- support vector
- machine learning