Composition of kernel and acquisition functions for High Dimensional Bayesian Optimization.
Antonio CandelieriIlaria GiordaniRiccardo PeregoFrancesco ArchettiPublished in: CoRR (2020)
Keyphrases
- high dimensional
- kernel function
- kernel space
- optimization algorithm
- feature space
- input space
- optimization problems
- kernel machines
- global optimization
- optimization process
- maximum likelihood
- dimensionality reduction
- efficient optimization
- high dimensional feature space
- bayesian learning
- gaussian processes
- additive models
- optimization method
- kernel methods
- similarity search
- low dimensional
- multi dimensional
- support vector
- parameter space
- bayesian networks
- high dimensional data
- hilbert space
- nearest neighbor
- evolutionary algorithm
- optimal kernel