High Dimensional Bayesian Optimization with Kernel Principal Component Analysis.
Kirill AntonovElena RaponiHao WangCarola DoerrPublished in: CoRR (2022)
Keyphrases
- kernel principal component analysis
- high dimensional
- discriminant analysis
- kernel pca
- feature space
- kernel function
- principal components
- feature extraction
- principal component analysis
- preprocessing
- kernel methods
- classification method
- dimensionality reduction
- kernel matrix
- low dimensional
- face recognition
- similarity search
- linear discriminant analysis
- feature vectors
- high dimensional feature space
- decision trees
- input space
- support vector machine svm
- classification algorithm
- data sets
- pattern recognition
- learning algorithm