Research map / Learning theory and algorithms / Combinatorial and search optimization
An Exact Algorithm with New Upper Bounds for the Maximum k-Defective Clique Problem in Massive Sparse Graphs
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use KDBB instead of MADEC+ with preprocessing | Maximum k-defective clique solving · Facebook instances, k = 10 | instances solved: 9 -> 109 | Helped |
| Use KDBB instead of MADEC+ with preprocessing | Maximum k-defective clique solving · 139 massive sparse graphs, k = 5 | instances solved: 81 -> 104 | Helped |
| Use KDBB instead of MADEC+ with preprocessing | Maximum k-defective clique solving · DIMACS10 and SNAP instances, k = 5 | instances solved: 28 -> 34 | Helped |
| Replace the candidate-based bound with the c-color bound (ablation) | KDBB · Facebook instances, k = 1 | average runtime (s): 561.21 -> 572.81 | Hurt |
| Replace the candidate-based bound with the c-color bound (ablation) | KDBB · Facebook instances, k = 3 | instances solved: 110 -> 97 | Hurt |
| Replace the candidate-based bound with the c-color bound (ablation) | KDBB · Facebook instances, k = 5 | average runtime (s): 926.60 -> 4677.43 | Hurt |
| Replace the candidate-based bound with the c-color bound (ablation) | KDBB · Facebook instances, k = 10 | instances solved: 109 -> 19 | Hurt |
| Add edge reduction to vertex reduction in preprocessing (ablation) | KDBB preprocessing · Facebook instances, k = 1 | vertices remaining (socfb-FSU53): 7585 -> 525 | Helped |
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