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CPC
2006

Solving Sparse Random Instances of Max Cut and Max 2-CSP in Linear Expected Time

9 years 3 months ago
Solving Sparse Random Instances of Max Cut and Max 2-CSP in Linear Expected Time
Abstract. We show that a maximum cut of a random graph below the giantcomponent threshold can be found in linear space and linear expected time by a simple algorithm. In fact, the algorithm solves a more general class of problems, namely binary 2-variable constraint satisfaction problems. In addition to Max Cut, such Max 2-CSPs encompass Max Dicut, Max 2-Lin, Max 2-Sat, Max-Ones-2-Sat, maximum independent set, and minimum vertex cover. We show that if a Max 2-CSP instance has an "underlying" graph which is a random graph G G(n, c/n), then the instance is solved in linear expected
Alexander D. Scott, Gregory B. Sorkin
Added 11 Dec 2010
Updated 11 Dec 2010
Type Journal
Year 2006
Where CPC
Authors Alexander D. Scott, Gregory B. Sorkin
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