Upper and Lower Bounds on the Performance of Kernel PCA.
Maxime HaddoucheBenjamin GuedjOmar RivasplataJohn Shawe-TaylorPublished in: CoRR (2020)
Keyphrases
- upper and lower bounds
- kernel pca
- upper bound
- kernel methods
- lower bound
- principal component analysis
- face recognition
- kernel principal component analysis
- spectral clustering
- kernel matrix
- lower and upper bounds
- dimensionality reduction
- feature space
- kernel function
- input space
- sample complexity
- support vector machine
- linear discriminant analysis
- feature extraction
- component analysis
- training samples
- face images
- small number
- pattern recognition
- computer vision