Research map / Learning theory and algorithms / Combinatorial and search optimization
Analysis of Pure Literal Elimination Rule for Non-uniform Random (MAX) k-SAT Problem with an Arbitrary Degree Distribution
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use rapidly decaying degree distributions rather than heavy-tailed distributions | Pure literal elimination · Random 3-CNF configuration model, average degree γ = 5 | clauses satisfied | Helped |
| Use a heavy-tailed zeta degree distribution rather than a Poisson degree distribution | Pure literal elimination · Random 3-CNF configuration model, γ > 10 | clauses satisfied | Helped |
| Increase average degree for rapidly decaying degree distributions | Pure literal elimination · Random 3-CNF configuration model, Poisson and subgaussian degrees | clauses satisfied | Hurt |
| Increase average degree for heavy-tailed degree distributions | Pure literal elimination · Random 3-CNF configuration model, log-normal and zeta degrees | clauses satisfied | Mixed |
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