Bayesian Optimization on GP-sampled functions sigma=3x10^-3, D=2, known hyperparameters
5.3Mean Stopping IterationOracler
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| OraclerKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Known2026.05 | 5.3 | 100 | 0.013 | |
| PRBKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Known2026.05 | 5.5 | 96 | 0.0175 | |
| ∆ESKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Known2026.05 | 5.7 | 92 | 0.0266 | |
| ∆CBKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Known2026.05 | 7.6 | 98 | 0.0118 | |
| AcqKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Known2026.05 | 83.7 | 94 | 0.0191 | |
| UCBbrKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Known2026.05 | 104.6 | 100 | 0.0031 | |
| NOSTOPKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Known2026.05 | 128 | 100 | 0.0031 |