SIAM Journal on Computing
The degree sequence of a scale-free random graph process
Random Structures & Algorithms
Some optimal inapproximability results
Journal of the ACM (JACM)
Measure and conquer: a simple O(20.288n) independent set algorithm
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Parameterized Complexity: The Main Ideas and Some Research Frontiers
ISAAC '01 Proceedings of the 12th International Symposium on Algorithms and Computation
A better approximation ratio for the vertex cover problem
ICALP'05 Proceedings of the 32nd international conference on Automata, Languages and Programming
Parameterized Complexity
A novel parameterised approximation algorithm for minimum vertex cover
Theoretical Computer Science
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We examine the behavior of two kernelization techniques for the vertex cover problem viewed as preprocessing algorithms. Specifically, we deal with the kernelization algorithms of Buss and of Nemhauser & Trotter. Our evaluation is applied to random graphs generated under the preferred attachment model, which is usually met in real word applications such as web graphs and others. Our experiments indicate that, in this model, both kernelization algorithms (and, specially, the Nemhauser & Trotter algorithm) reduce considerably the input size of the problem and can serve as very good preprocessing algorithms for vertex cover, on the preferential attachment graphs.