Computing with unreliable information

Uriel Feige; David Peleg; Prabhakar Raghavan; Eli Upfal

doi:10.1145/100216.100230

Computing with unreliable information

Uriel Feige
, David Peleg
, Prabhakar Raghavan
, Eli Upfal

Weizmann Institute of Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Scopus citations

Abstract

A (possibly randomized) computation tree is considered in which each node gives the correct answer with some probability ≥ p, where p is a fixed constant in ( 1/2 , 1), bounded away from 1/2 and 1. The node faults are independent. The depth of the computation tree is studied in terms of a tolerance parameter Q member of (0, 1/2 ): on any instance, the computation tree leads to a leaf giving the correct answer on that instance with probability at least 1 - Q. The success probability of the algorithm is computed over the combined probability space of the outcome of individual comparisons and the results of coinflips (in case our algorithm is randomized). Noisy comparison trees are studied for problems such as sorting, selection and searching.

Original language	English
Title of host publication	Proceedings of the twenty-second annual ACM symposium on Theory of Computing
Publisher	Publ by ACM
Pages	128-137
Number of pages	10
ISBN (Print)	0897913612, 9780897913614
DOIs	https://doi.org/10.1145/100216.100230
State	Published - 1990
Externally published	Yes
Event	22nd Annual ACM Symposium on Theory of Computing, STOC 1990 - Baltimore, MD, USA Duration: 14 May 1990 → 16 May 1990

Publication series

Name	Proceedings of the twenty-second annual ACM symposium on Theory of Computing

Conference

Conference	22nd Annual ACM Symposium on Theory of Computing, STOC 1990
City	Baltimore, MD, USA
Period	14/05/90 → 16/05/90

Access to Document

10.1145/100216.100230

Cite this

@inproceedings{d64c649b8ffa4d78b698379fa892c1b7,

title = "Computing with unreliable information",

abstract = "A (possibly randomized) computation tree is considered in which each node gives the correct answer with some probability ≥ p, where p is a fixed constant in ( 1/2 , 1), bounded away from 1/2 and 1. The node faults are independent. The depth of the computation tree is studied in terms of a tolerance parameter Q member of (0, 1/2 ): on any instance, the computation tree leads to a leaf giving the correct answer on that instance with probability at least 1 - Q. The success probability of the algorithm is computed over the combined probability space of the outcome of individual comparisons and the results of coinflips (in case our algorithm is randomized). Noisy comparison trees are studied for problems such as sorting, selection and searching.",

author = "Uriel Feige and David Peleg and Prabhakar Raghavan and Eli Upfal",

year = "1990",

doi = "10.1145/100216.100230",

language = "אנגלית",

isbn = "0897913612",

series = "Proceedings of the twenty-second annual ACM symposium on Theory of Computing",

publisher = "Publ by ACM",

pages = "128--137",

booktitle = "Proceedings of the twenty-second annual ACM symposium on Theory of Computing",

note = "22nd Annual ACM Symposium on Theory of Computing, STOC 1990 ; Conference date: 14-05-1990 Through 16-05-1990",

}

Feige, U, Peleg, D, Raghavan, P & Upfal, E 1990, Computing with unreliable information. in Proceedings of the twenty-second annual ACM symposium on Theory of Computing. Proceedings of the twenty-second annual ACM symposium on Theory of Computing, Publ by ACM, pp. 128-137, 22nd Annual ACM Symposium on Theory of Computing, STOC 1990, Baltimore, MD, USA, 14/05/90. https://doi.org/10.1145/100216.100230

Computing with unreliable information. / Feige, Uriel; Peleg, David; Raghavan, Prabhakar et al.
Proceedings of the twenty-second annual ACM symposium on Theory of Computing. Publ by ACM, 1990. p. 128-137 (Proceedings of the twenty-second annual ACM symposium on Theory of Computing).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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ER -

Computing with unreliable information

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