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Research map / Learning theory and algorithms / Combinatorial and search optimization

FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints

AAAI 2020 · Learning theory and algorithms › Combinatorial and search optimization · approach: SAT and model counting solvers · 9 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use FourierSAT instead of MonoSATSolving minimum vertex covering constraints · Minimum vertex coveringproblems solved: 420 -> 472Helped
Use FourierSAT instead of MiniCARDSolving minimum vertex covering constraints · Minimum vertex coveringproblems solved: 261 -> 472Helped
Use FourierSAT instead of WalkSAT with CNF encodingParity learning with error · Parity learning with errorproblems solved: 79 -> all 300Helped
Use FourierSAT instead of WalkSAT with Sequential Counter encodingRandom CNF-XOR-CARD formulas · Random CNF-XOR-CARD formulasproblems solved: 2272 -> 2957Helped
Use FourierSAT instead of WalkSAT with Sorting Network encodingRandom CNF-XOR-CARD formulas · Random CNF-XOR-CARD formulasproblems solved: 2444 -> 2957Helped
Use FourierSAT instead of WalkSAT with Totalizer encodingRandom CNF-XOR-CARD formulas · Random CNF-XOR-CARD formulasproblems solved: 2452 -> 2957Helped
Use FourierSAT instead of WalkSAT with any tested cardinality encoding except Sequential CounterRandom vertex-covering benchmarks · Minimum vertex coveringproblems solvedHelped
Use FourierSAT instead of Cryptominisat on parity learning with CNF+XORParity learning with error · Parity learning with errorproblems solvedNo clear effect
Use FourierSAT instead of Cryptominisat on parity learning with pure CNFParity learning with error · Parity learning with errorproblems solvedHelped
Use FourierSAT instead of CryptominisatRandom hybrid constraints · Random CNF-XOR-CARD formulasproblems solvedHurt

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