Extracting randomness: how and why a survey

Noam Nisan*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

63 Scopus citations

Abstract

Extractors are boolean functions that allow, in some precise sense, extraction of randomness from somewhat random distributions. Extractors, and the closely related 'Dispersers', exhibit some of the most 'random-like' properties of explicitly constructed combinatorial structures. In turn, extractors and dispersers have many applications in 'removing randomness' in various settings, and in making randomized constructions explicit. This manuscript survey extractors and dispersers: what they are, how they can be designed, and some of their applications. The work described is due to of a long list of research papers by various authors - most notably by David Zuckerman.

Original languageAmerican English
Pages (from-to)44-58
Number of pages15
JournalProceedings of the Annual IEEE Conference on Computational Complexity
StatePublished - 1996
EventProceedings of the 1996 11th Annual IEEE Conference on Computational Complexity - Philadelphia, PA, USA
Duration: 24 May 199627 May 1996

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