Constraint Learning on Random constraints Binary synthetic (test)
97.8Vector AccuracyILP–Loss
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| ILP–LossNumber of ground truth constraints=12022.10 | 97.8 | 7.3 | |
| CombOptNetNumber of ground truth constraints=12022.10 | 97.6 | 8.2 | |
| ILP–LossNumber of ground truth constraints=22022.10 | 96 | 11.6 | |
| CombOptNetNumber of ground truth constraints=22022.10 | 95.3 | 13.5 | |
| ILP–LossNumber of ground truth constraints=42022.10 | 92.8 | 18.1 | |
| ILP–LossNumber of ground truth constraints=82022.10 | 87.8 | 27.5 | |
| CombOptNetNumber of ground truth constraints=42022.10 | 84.3 | 26.5 | |
| CombOptNetNumber of ground truth constraints=82022.10 | 63.4 | 40.8 |