Research map / Probabilistic and scientific modeling / Bayesian optimization
Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use BADS instead of other tested optimizers | BADS · BBOB09 noiseless | fraction of successful runs | Mixed |
| Use BADS instead of other tested optimizers | BADS · BBOB09 noisy, heteroskedastic | fraction of successful runs | Helped |
| Use BADS instead of other tested optimizers | BADS · CCN17 real model-fitting problems | optimization performance | Helped |
| Use hybrid local BO with MADS polling instead of vanilla BO | CCN17 real model-fitting problems · CCN17 | optimization performance | Helped |
| Replace the default RQ kernel and LCB acquisition combination with alternative kernel/acquisition choices (ablation) | BADS · BBOB09 noiseless | fraction of successful runs | Hurt |
| Set the number of search steps to 1 (ablation) | BADS · BBOB09 noiseless | fraction of successful runs | Hurt |
| Fix the search covariance matrix to the length-scale matrix (ablation) | BADS · BBOB09 noiseless | fraction of successful runs | Hurt |
| Fix the search covariance matrix to the weighted covariance matrix (ablation) | BADS · BBOB09 noiseless | fraction of successful runs | Hurt |
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