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Parameterized Compilation Lower Bounds for Restricted CNF-formulas
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Parameterized Compilation Lower Bounds for Restricted CNF-formulas
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We show unconditional parameterized lower bounds in the area of knowledge compilation, more specifically on the size of circuits in decomposable negation normal form (DNNF) that encode CNF-formulas restricted by several graph width measures. In particular, we show that - there are CNF formulas of size $n$ and modular incidence treewidth $k$ whose smallest DNNF-encoding has size $n^{\Omega(k)}$, and - there are CNF formulas of size $n$ and incidence neighborhood diversity $k$ whose smallest DNNF-encoding has size $n^{\Omega(\sqrt{k})}$. These results complement recent upper bounds for compiling CNF into DNNF and strengthen---quantitatively and qualitatively---known conditional low\-er bounds for cliquewidth. Moreover, they show that, unlike for many graph problems, the parameters considered here behave significantly differently from treewidth.
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Cited by 1 Pith paper
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A Distributed Framework for Compiling and Reasoning with d-DNNF
A Cube-and-Conquer framework compiles CNF formulas into a virtual d-DNNF distributed across workers, enabling counting, direct access, and uniform sampling under conditioning.
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