High Dimensional Bayesian Optimization with Kernel Principal Component Analysis.
Kirill AntonovElena RaponiHao WangCarola DoerrPublished in: PPSN (1) (2022)
Keyphrases
- kernel principal component analysis
- high dimensional
- kernel pca
- preprocessing
- discriminant analysis
- principal component analysis
- feature extraction
- principal components
- kernel methods
- kernel function
- feature space
- kernel matrix
- low dimensional
- classification method
- high dimensional feature space
- data sets
- input space
- high dimensional data
- dimensionality reduction
- linear discriminant analysis
- support vector
- support vector machine svm
- training data
- data analysis
- data points