Bayesian Optimization on GP-sampled functions sigma=5x10^-3, D=2, known hyperparameters
5.8Mean Stopping Iteration∆ES
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| ∆ESKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Known2026.05 | 5.8 | 88 | 0.0332 | |
| PRBKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Known2026.05 | 6.2 | 94 | 0.0226 | |
| OraclerKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Known2026.05 | 7.7 | 98 | 0.0189 | |
| ∆CBKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Known2026.05 | 11.4 | 98 | 0.0125 | |
| AcqKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Known2026.05 | 83.7 | 92 | 0.0235 | |
| UCBbrKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Known2026.05 | 124.1 | 98 | 0.0112 | |
| NOSTOPKernel=SE kernel, Dimension (D)=2, Budget (T)=128, Hyperparameter Knowledge=Known2026.05 | 128 | 98 | 0.0094 |