Research map / Graph learning / Graph algorithms and clustering
(Nearly) Efficient Algorithms for the Graph Matching Problem on Correlated Random Graphs
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use a large family of strictly balanced, asymmetric test graphs and aggregate their subgraph-count correlations | Correlated Erdős-Rényi graph distinguishing · Correlated vs. null Erdős-Rényi graphs | distinguishing success probability: at least 0.9 | Helped |
| Use logarithmic-size test graphs to cover vertices, then boost the partial matching | Correlated Erdős-Rényi graph matching · Correlated Erdős-Rényi recovery; stated parameter regimes | exact permutation recovery | Helped |
| Replace requiring a supplied seed set with test-subgraph-based initialization | Correlated Erdős-Rényi graph matching · Correlated Erdős-Rényi recovery | runtime: n^{O(log n)} | Helped |
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