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Smoothed analysis of algorithms: why the simplex algorithm usually takes polynomial time

Authors: Daniel A. Spielman Shang-hua Teng The Pennsylvania State University CiteSeerX Archives

Contributors: Daniel A. Spielman Shang-hua Teng The Pennsylvania State University CiteSeerX Archives

Source: http://www.cs.duke.edu/courses/spring07/cps296.2/papers/p385-a_spielman.pdf.

Subject Terms: Categories and Subject Descriptors, F.2.1 [Analysis of Algorithms and Problems Complexity, Numerical Algorithms and Problems, G.1.6 [Numerical Analysis, Optimization—linear programming General Terms, Algorithms, Theory Additional Key Words and Phrases, Simplex method, smoothed analysis, complexity, perturbation

File Description: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.86.4665

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.86.4665
http://www.cs.duke.edu/courses/spring07/cps296.2/papers/p385-a_spielman.pdf

Smoothed Analysis of Algorithms: Why the Simplex Algorithm Usually Takes Polynomial Time.

Authors: Spielman, Daniel A. Shang-Hua Thng

Source: Journal of the ACM; May2004, Vol. 51 Issue 3, p385-463, 79p

Subject Terms: ALGORITHMS, SIMPLEXES (Mathematics), POLYNOMIALS, STANDARD deviations, INTERPOLATION spaces, GAUSSIAN processes, DISTRIBUTION (Probability theory), ANALYSIS of variance