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Abstract: We point out how the methods of Nisan [Nis90, Nis92], originally developed for derandomizing space-bounded computations, may be applied to obtain polynomial-time and NC derandomizations of several probabilistic algorithms. Our list includes the randomized rounding steps of linear and semi-definite programming relaxations of optimization problems, parallel derandomization of discrepancy-type problems, and the Johnson--Lindenstrauss lemma, to name a few. (Update)
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BibTeX entry: (Update)
D. Sivakumar. Algorithmic derandomization via complexity theory. In Proceedings of the 34th annual ACM Symposium on Theory of Computing (STOC), pages 619--626, 2002. http://citeseer.ist.psu.edu/sivakumar02algorithmic.html More
@misc{ sivakumar02algorithmic,
author = "D. Sivakumar",
title = "Algorithmic derandomization via complexity theory",
text = "D. Sivakumar. Algorithmic derandomization via complexity theory. In Proceedings
of the 34th annual ACM Symposium on Theory of Computing (STOC), pages 619--626,
2002.",
year = "2002",
url = "citeseer.ist.psu.edu/sivakumar02algorithmic.html" }
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