Bayesian Optimization on GP-sampled functions sigma=3x10^-3, D=6, known hyperparameters
14.1Mean Stopping IterationOracler
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| OraclerKernel=SE kernel, Dimension (D)=6, Budget (T)=512, Hyperparameter Knowledge=Known2026.05 | 14.1 | 100 | 0.0294 | |
| ∆ESKernel=SE kernel, Dimension (D)=6, Budget (T)=512, Hyperparameter Knowledge=Known2026.05 | 14.1 | 82 | 0.0461 | |
| PRBKernel=SE kernel, Dimension (D)=6, Budget (T)=512, Hyperparameter Knowledge=Known2026.05 | 14.6 | 94 | 0.0315 | |
| ∆CBKernel=SE kernel, Dimension (D)=6, Budget (T)=512, Hyperparameter Knowledge=Known2026.05 | 18.9 | 98 | 0.0173 | |
| UCBbrKernel=SE kernel, Dimension (D)=6, Budget (T)=512, Hyperparameter Knowledge=Known2026.05 | 25.9 | 98 | 0.0132 | |
| AcqKernel=SE kernel, Dimension (D)=6, Budget (T)=512, Hyperparameter Knowledge=Known2026.05 | 253.6 | 84 | 0.0407 | |
| NOSTOPKernel=SE kernel, Dimension (D)=6, Budget (T)=512, Hyperparameter Knowledge=Known2026.05 | 512 | 100 | 0.003 |