A Kernel for Hierarchical Parameter Spaces
arXiv:1310.5738
Abstract
We define a family of kernels for mixed continuous/discrete hierarchical parameter spaces and show that they are positive definite.
Cited by in corpus (7)
- A Framework to Integrate Mode Choice in the Design of Mobility-on-Demand Systems
- Bayesian Optimization of Combinatorial Structures
- Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces
- HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO
- Additive Tree-Structured Conditional Parameter Spaces in Bayesian Optimization: A Novel Covariance Function and a Fast Implementation
- Deep-n-Cheap: An Automated Search Framework for Low Complexity Deep Learning
- A First Analysis of Kernels for Kriging-based Optimization in Hierarchical Search Spaces