Research map / Learning theory and algorithms / Combinatorial and search optimization
Warmstarting of Model-Based Algorithm Configuration
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Warmstart configuration with INIT, DMW, and their combination IDMW | SMAC configuring SparrowToRiss · BMC, 3cnf, 5SAT500, and 7SAT90 | PAR10 | Helped |
| Combine INIT and DMW as IDMW | SMAC configuring SparrowToRiss · 12 SAT tasks | geometric-average speedup: 4.3 | Helped |
| Add previous-run incumbents and a complementary configuration set to the initial design (INIT) (ablation) | SMAC configuring SparrowToRiss · BMC | PAR10: 209.6 -> 203.1 | Helped |
| Add previous-run performance models, weighted using current-run validation data (DMW) (ablation) | SMAC configuring SparrowToRiss · BMC | PAR10: 209.6 -> 155.9 | Helped |
| Use INIT and DMW together (IDMW) (ablation) | SMAC configuring SparrowToRiss · BMC | PAR10: 209.6 -> 137.4 | Helped |
| Use IDMW instead of default SMAC | SMAC configuring SparrowToRiss · LABS | PAR10: 232.9 -> 286.7 | Hurt |
| Use IDMW instead of default SMAC | SMAC configuring SparrowToRiss · N-Rooks | PAR10: 8.6 -> 12.7 | Hurt |
| Use IDMW warmstarting | SMAC configuring SparrowToRiss · LABS and N-Rooks | speedup over default SMAC: 0.8; 0.5 | Hurt |
| Combine INIT and DMW as IDMW | SMAC configuring SparrowToRiss · 7SAT90 | speedup over default SMAC: 165.3 | Helped |
| Use previous-benchmark data in DMW, with model weights adapted to current observations (ablation) | SMAC configuring SparrowToRiss · UNSAT-k5 using K3 and 3cnf history | PAR10 | No clear effect |
| Use AAF rather than default SMAC | SMAC configuring SparrowToRiss · LABS | PAR10: 232.9 -> 291.2 | Hurt |
| Use INIT rather than default SMAC (ablation) | SMAC configuring SparrowToRiss · LABS | PAR10: 232.9 -> 271.2 | Hurt |
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