Approximate weighted model integration on DNF structures
Weighted model counting consists of computing the weighted sum of all satisfying assignments of a propositional formula. Weighted model counting is well-known to be #P-hard for exact solving, but admits a fully polynomial randomized approximation scheme when restricted to DNF structures. In this wor...
Main Authors: | Abboud, R, Ceylan, İİ, Dimitrov, R |
---|---|
Format: | Journal article |
Language: | English |
Published: |
Elsevier
2022
|
Similar Items
-
Learning to reason: Leveraging neural networks for approximate DNF counting
by: Abboud, R, et al.
Published: (2020) -
BoxE: A box embedding model for knowledge base completion
by: Abboud, R, et al.
Published: (2020) -
The surprising power of graph neural networks with random node initialization
by: Abboud, R, et al.
Published: (2021) -
A STRUCTURED APPROXIMATION PROBLEM WITH APPLICATIONS TO FREQUENCY WEIGHTED MODEL-REDUCTION
by: Glover, K, et al.
Published: (1992) -
Approximating the singular integrals of Cauchy type with weight function on the interval.
by: Eshkuratov, Zainidin K., et al.
Published: (2011)