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• W2963010019 abstract "We prove super-polynomial lower bounds on the size of linear programming relaxations for approximation versions of constraint satisfaction problems. We show that for these problems, polynomial-sized linear programs are no more powerful than programs arising from a constant number of rounds of the Sherali--Adams hierarchy. In particular, any polynomial-sized linear program for M ax C ut has an integrality gap of ½ and any such linear program for M ax 3-S at has an integrality gap of ⅞." @default.
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• W2963010019 date "2016-10-26" @default.
• W2963010019 modified "2023-10-05" @default.
• W2963010019 title "Approximate Constraint Satisfaction Requires Large LP Relaxations" @default.
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• W2963010019 doi "https://doi.org/10.1145/2811255" @default.
• W2963010019 hasPublicationYear "2016" @default.
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