Research map / Probabilistic and scientific modeling / Bayesian optimization
Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| USeMO vs PESMO | multi-objective BO · PRDZPS-6,6 | acquisition optimization time (s): 110.4 -> 13.9 | Helped |
| USeMO vs SMSego | multi-objective BO · DTLZ1 | acquisition optimization time (s): 215 -> 9 | Helped |
| USeMO vs ParEGO | multi-objective BO · ARS-3,5 | acquisition optimization time (s): 6.7 -> 7.0 | No clear effect |
| USeMO vs baselines (PESMO, ParEGO, SMSego, EHI, SUR) | multi-objective BO · synthetic and 6 real-world benchmarks | hypervolume difference / R2 | Helped |
| select by uncertainty maximization instead of random from cheap Pareto set (ablation) | USeMO · synthetic benchmarks | hypervolume difference | Helped |
| increase NSGA-II function calls from 1,000 to 20,000 | USeMO cheap MO solver · benchmarks | performance | No clear effect |
| use different acquisition functions (TS vs EI) | USeMO · benchmarks | convergence | No clear effect |
| ParEGO random scalarization vs USeMO | multi-objective BO · benchmarks | hypervolume difference | Mixed |
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