Self-Predicting Boolean Functions

Nir Weinberger, Ofer Shayevitz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A Boolean function g is said to be an optimal predictor for another Boolean function f, if it minimizes the probability that f(X^{n})\neq g(Y^{n}) among all functions, where X^{n} is uniform over the Hamming cube and Y^{n} is obtained from X^{n} by independently flipping each coordinate with probability \delta. This paper is about self-predicting functions, which are those that coincide with their optimal predictor.

Original languageEnglish
Title of host publication2018 IEEE International Symposium on Information Theory, ISIT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages276-280
Number of pages5
ISBN (Print)9781538647806
DOIs
StatePublished - 15 Aug 2018
Event2018 IEEE International Symposium on Information Theory, ISIT 2018 - Vail, United States
Duration: 17 Jun 201822 Jun 2018

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2018-June
ISSN (Print)2157-8095

Conference

Conference2018 IEEE International Symposium on Information Theory, ISIT 2018
Country/TerritoryUnited States
CityVail
Period17/06/1822/06/18

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