Date of Original Version

1-2002

Type

Conference Proceeding

Abstract or Description

The smoothed complexity [1] of an algorithm is the expected running time of the algorithm on an arbitrary instance under a random perturbation. It was shown recently that the simplex algorithm has polynomial smoothed complexity. We show that a simple greedy algorithm for linear programming, the perceptron algorithm, also has polynomial smoothed complexity, in a high probability sense; that is, the running time is polynomial with high probability over the random perturbation.

DOI

10.1145/550000/545499

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Published In

Proceedings of the Thirteenth Annual ACM-SIAM Symposium on Discrete Algorithms , 905-914.