Computing with noisy information

Uriel Feige, Prabhakar Raghavan, David Peleg, Eli Upfal

Research output: Contribution to journalArticlepeer-review

212 Scopus citations


This paper studies the depth of noisy decision trees in which each node gives the wrong answer with some constant probability. In the noisy Boolean decision tree model, tight bounds are given on the number of queries to input variables required to compute threshold functions, the parity function and symmetric functions. In the noisy comparison tree model, tight bounds are given on the number of noisy comparisons for searching, sorting, selection and merging. The paper also studies parallel selection and sorting with noisy comparisons, giving tight bounds for several problems.

Original languageEnglish
Pages (from-to)1001-1018
Number of pages18
JournalSIAM Journal on Computing
Issue number5
StatePublished - 1994
Externally publishedYes


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