Research map / Probabilistic and scientific modeling / Bayesian optimization
Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| qEHVI with exact autodiff gradients vs PESMO | multi-objective BO · BraninCurrin (CPU, q=1) | wall time: 249.16 -> 3.63 | Helped |
| qEHVI vs all baselines | multi-objective BO · BraninCurrin, C2-DTLZ2, VehicleSafety, ABR | log hypervolume difference | Helped |
| use exact gradients instead of finite differences or CMA-ES for acquisition optimization (ablation) | EHVI/qEHVI · DTLZ2 | acquisition optimization time | Helped |
| sequential greedy with integration over pending points instead of posterior mean or joint optimization (ablation) | qEHVI · DTLZ2 | hypervolume | Helped |
| increase batch size q | qEHVI · ABR | sample complexity per evaluation | No clear effect |
| TS-TCH instead of qEHVI | multi-objective BO · all benchmarks | wall time vs optimization performance | Mixed |
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