Variable selection for Gaussian process regression through a sparse projection.
Chiwoo ParkDavid J. BorthNicholas S. WilsonChad N. HunterPublished in: CoRR (2020)
Keyphrases
- variable selection
- gaussian process regression
- covariance function
- high dimensional
- group lasso
- sparsity inducing
- gaussian process
- input variables
- gaussian processes
- cross validation
- model selection
- structured sparsity
- dimension reduction
- high dimensional data
- dimensionality reduction
- low dimensional
- prior knowledge
- sparse regression
- image processing
- high dimensionality
- data mining
- nearest neighbor
- decision trees
- feature selection