Research map / Learning theory and algorithms / Combinatorial and search optimization
Combinatorial Persistency Criteria for Multicut and Max-Cut
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Apply the proposed persistency criteria instead of prior criteria [2, 29] | Multicut instances · Multicut benchmarks in Table 2 | remaining graph size | Helped |
| Apply the proposed persistency method | Ising Chain · Ising Chain | remaining nodes and edges: 0.0% | Helped |
| Apply the proposed persistency method | 2D Torus · 2D Torus | remaining graph size: 23.6%; 27.9% | Helped |
| Apply the proposed persistency method | 3D Torus · 3D Torus | remaining graph size: 94.8%; 98.1% | Hurt |
| Apply the proposed method rather than QPBO [34] | Deconvolution · Deconvolution | remaining graph size: 61.0%; 56.5% | No clear effect |
| Apply the proposed method rather than QPBO [34] | Super Resolution · Super Resolution | remaining graph size: 0.0% vs 0.2%; 0.0% vs 0.1% | Helped |
| Apply the proposed method rather than QPBO [34] | Texture Restoration · Texture Restoration | remaining graph size: 98.4%; 98.5% vs 58.8%; 57.3% | Mixed |
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