Composition of Kernel and Acquisition Functions for High Dimensional Bayesian Optimization.
Antonio CandelieriIlaria GiordaniRiccardo PeregoFrancesco ArchettiPublished in: LION (2020)
Keyphrases
- high dimensional
- optimization algorithm
- kernel space
- kernel function
- feature space
- optimization problems
- kernel machines
- gaussian processes
- similarity search
- high dimensionality
- optimization process
- multi dimensional
- optimal kernel
- kernel methods
- input space
- support vector
- additive models
- bayesian learning
- constrained optimization
- microarray data
- optimization method
- maximum likelihood
- nearest neighbor
- data points
- variable selection
- posterior probability
- web service composition
- basis functions
- kernel principal component analysis
- efficient optimization