Bayesian Optimization on GP-sampled functions sigma=5x10^-3, D=6, known hyperparameters
14Mean Stopping Iteration∆ES
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| ∆ESKernel=SE kernel, Dimension (D)=6, Budget (T)=512, Hyperparameter Knowledge=Known2026.05 | 14 | 68 | 0.0697 | |
| PRBKernel=SE kernel, Dimension (D)=6, Budget (T)=512, Hyperparameter Knowledge=Known2026.05 | 16.4 | 94 | 0.0293 | |
| OraclerKernel=SE kernel, Dimension (D)=6, Budget (T)=512, Hyperparameter Knowledge=Known2026.05 | 25 | 98 | 0.0304 | |
| ∆CBKernel=SE kernel, Dimension (D)=6, Budget (T)=512, Hyperparameter Knowledge=Known2026.05 | 28.9 | 96 | 0.0184 | |
| UCBbrKernel=SE kernel, Dimension (D)=6, Budget (T)=512, Hyperparameter Knowledge=Known2026.05 | 35.3 | 94 | 0.018 | |
| AcqKernel=SE kernel, Dimension (D)=6, Budget (T)=512, Hyperparameter Knowledge=Known2026.05 | 253.6 | 72 | 0.0613 | |
| NOSTOPKernel=SE kernel, Dimension (D)=6, Budget (T)=512, Hyperparameter Knowledge=Known2026.05 | 512 | 98 | 0.0089 |