Research map / Probabilistic and scientific modeling / Bayesian optimization
Mercer Features for Efficient Combinatorial Bayesian Optimization
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use MerCBO instead of prior methods | combinatorial Bayesian optimization · Ising sparsification | objective value | Helped |
| Use MerCBO instead of prior methods | combinatorial Bayesian optimization · LABS, 40 dimensions | Merit factor | Mixed |
| Use MerCBO instead of prior methods | combinatorial Bayesian optimization · LABS, 50 dimensions | Merit factor | Helped |
| Use MerCBO instead of COMBO | combinatorial Bayesian optimization · UAV power-system design, total energy | optimization performance | Mixed |
| Use MerCBO instead of COMBO | combinatorial Bayesian optimization · UAV power-system design, mass | optimization performance | Mixed |
| Use parallel Thompson sampling instead of parallel expected improvement | MerCBO · DNA sequence design, one transcription factor | optimization performance | Hurt |
| Use parallel Thompson sampling instead of parallel expected improvement | MerCBO · DNA sequence design | mean Hamming distance | Helped |
| Increase batch size | parallel Thompson sampling · DNA sequence design, six transcription factors | optimization performance | Mixed |
| Increase batch size | parallel sequence design · DNA sequence design | mean Hamming distance | Helped |
| Use second-order Mercer features instead of higher-order features (ablation) | MerCBO · combinatorial Bayesian optimization benchmarks | optimization performance | Helped |
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