Research map / Learning theory and algorithms / Clustering
Partial Optimality in Cubic Correlation Clustering
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Increase noise parameter α | All partial-optimality conditions · Partition dataset | percentage of fixed variables | Hurt |
| Increase noise parameter α | All partial-optimality conditions · Partition dataset | runtime | Hurt |
| Introduce triple costs by increasing β | All partial-optimality conditions · Partition dataset | percentage of fixed variables | Hurt |
| Apply cut conditions | Partial-optimality testing · Partition dataset | variables fixed | Helped |
| Apply join conditions other than the simplified subset-based join condition | Partial-optimality testing · Partition dataset | variables fixed | No clear effect |
| Use the simplified subset-based join condition | Partial-optimality testing · Partition dataset | variables fixed | Helped |
| Increase instance size | All partial-optimality conditions · Partition dataset | variables fixed | Hurt |
| Increase instance size | All partial-optimality conditions · Partition dataset | runtime | Hurt |
| Increase noise parameter σ | All partial-optimality conditions · Geometric dataset | percentage of fixed variables | Hurt |
| Increase noise parameter σ | All partial-optimality conditions · Geometric dataset | runtime | Hurt |
| Apply cut conditions | Partial-optimality testing · Geometric dataset | variables fixed | Helped |
| Use the simplified subset-based join condition | Partial-optimality testing · Geometric dataset | variables fixed | Helped |
Closest papers by meaning
- Partial Optimality and Fast Lower Bounds for Weighted Correlation Clustering (ICML 2018 · similarity 0.92)
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- Towards Better-than-2 Approximation for Constrained Correlation Clustering (ICML 2025 · similarity 0.88)
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