Research map / Probabilistic and scientific modeling / Bayesian optimization
Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| batch size 4 instead of sequential MACE | MACE · Rosenbrock10 | final regret: 499.697 -> 158.116 | Helped |
| batch size 4 instead of sequential MACE | MACE · Branin | final regret: 1.05e-5 -> 4.62e-6 | Helped |
| batch size 4 instead of sequential MACE | MACE · operational amplifier | FOM: -678.174 -> -690.3 | Helped |
| batch size 4 instead of sequential MACE | MACE · class-E power amplifier | FOM: -4.08608 -> -4.31762 | Helped |
| batch size 4 reduces variance of final FOM | MACE · operational amplifier | FOM std: 21.7445 -> 0.104963 | Helped |
| MACE-1 versus sequential EI | EI-1 · Rosenbrock2 | final regret: 13.5508 -> 0.026173 | Helped |
| MACE-4 versus parallel EI-LP-4 | EI-LP-4 · Rosenbrock10 | final regret: 721.351 -> 158.116 | Helped |
| MACE-4 versus EI-LP-4 on Eggholder and Ackley2 | MACE-4 · Eggholder | final regret: 46.38 -> 44.68 | Hurt |
| MACE-4 versus qKG-4 | qKG-4 · Hartmann6 | final regret: 0.47134 -> 0.0275738 | Helped |
| MACE-4 versus BLCB-4 | BLCB-4 · class-E power amplifier | FOM: -4.20266 -> -4.31762 | Helped |
| MACE-1 versus sequential LCB on Ackley2 | MACE-1 · Ackley2 | final regret: 1.624 -> 1.71474 | Hurt |
| MACE versus other methods in compute overhead on Rosenbrock10 with B=4 | MACE · Rosenbrock10 | wall time: 11 hours vs 1 hour | Hurt |
Closest papers by meaning
- FALCON: An ML Framework for Fully Automated Layout-Constrained Analog Circuit Design (NeurIPS 2025 · similarity 0.82)
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