Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations.
Yifan ChenEthan N. EpperlyJoel A. TroppRobert J. WebberPublished in: CoRR (2022)
Keyphrases
- kernel matrix
- kernel methods
- low rank approximation
- kernel function
- low rank
- metric learning
- kernel learning
- feature space
- input space
- positive definite
- kernel matrices
- model selection
- training samples
- ls svm
- support vectors
- reproducing kernel hilbert space
- kernel pca
- support vector
- linear combination
- supervised learning
- feature extraction
- feature selection
- machine learning