The SKIM-FA Kernel: High-Dimensional Variable Selection and Nonlinear Interaction Discovery in Linear Time.
Raj AgrawalTamara BroderickPublished in: J. Mach. Learn. Res. (2023)
Keyphrases
- variable selection
- high dimensional
- high dimensional feature space
- kernel principal component analysis
- kernel function
- feature space
- kernel pca
- input variables
- cross validation
- dimension reduction
- low dimensional
- ls svm
- linear models
- group lasso
- kernel matrix
- dimensionality reduction
- input space
- high dimensionality
- model selection
- high dimensional data
- support vector
- knowledge discovery
- kernel methods
- nearest neighbor
- data points
- linear discriminant analysis
- number of input variables
- data sets
- multiple kernel learning
- gaussian processes
- pattern recognition
- computer vision