Bayesian Optimization on GP-sampled functions sigma=3x10^-3, D=2
5.4Mean Stopping Iteration∆ES
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| ∆ESKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Unknown2026.05 | 5.4 | 78 | 0.0662 | |
| ∆CBKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Unknown2026.05 | 7.6 | 90 | 0.0315 | |
| PRBKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Unknown2026.05 | 7.8 | 86 | 0.0434 | |
| OraclerKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Unknown2026.05 | 8.2 | 98 | 0.0362 | |
| UCBbrKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Unknown2026.05 | 76.6 | 96 | 0.0144 | |
| AcqKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Unknown2026.05 | 81.3 | 86 | 0.0374 | |
| NOSTOPKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Unknown2026.05 | 128 | 98 | 0.0081 |