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The power of randomness for communication complexity

Published: 01 January 1987 Publication History

Abstract

Improving a result of Mehlhorn and Schmidt, a function f with deterministic communication complexity n2 is shown to have Las Vegas communication complexity Ο(n). This is the best possible, because the deterministic complexity cannot be more than the square of the Las Vegas communication complexity for any function.

References

[1]
Aho, A.V., Ullman, J.D. & Yannakakis, M. (1983), On Notations of Information Transfer in VLSI Circuits, 15th STOC, 133-139.
[2]
Hardy & Wright (1979), An Introduction to the Theory of Numbers, 5th ed., Oxford.
[3]
Mehlhorn, K. & Schmidt, E.M. (1982), Las Vegas is better than Determinism in VLSI and Distributed Computing (Ex. Ab.), 14th STOC, 330-337.
[4]
Yao, A.C. (1979), Some Complexity Questions Related to Distributive Computing, llth STOC, 209-213.
[5]
Yao, A.C. (1981), The Entropic Limitations on VLSI Computation, 13th STOC, 308-311.

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cover image ACM Conferences
STOC '87: Proceedings of the nineteenth annual ACM symposium on Theory of computing
January 1987
471 pages
ISBN:0897912217
DOI:10.1145/28395
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 January 1987

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STOC '87 Paper Acceptance Rate 50 of 165 submissions, 30%;
Overall Acceptance Rate 1,469 of 4,586 submissions, 32%

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  • (2005)Optimal lower bounds on the multiparty communication complexitySTACS 9510.1007/3-540-59042-0_87(350-360)Online publication date: 1-Jun-2005
  • (2005)A time-randomness tradeoff for communication complexityDistributed Algorithms10.1007/3-540-54099-7_26(390-401)Online publication date: 8-Jun-2005
  • (2004)Multiparty communication complexity and very hard functionsInformation and Computation10.1016/j.ic.2004.03.002192:1(1-14)Online publication date: 1-Jul-2004
  • (2004)An Improved Communication-Randomness TradeoffLATIN 2004: Theoretical Informatics10.1007/978-3-540-24698-5_48(444-454)Online publication date: 2004
  • (2003)Two applications of information complexityProceedings of the thirty-fifth annual ACM symposium on Theory of computing10.1145/780542.780640(673-682)Online publication date: 9-Jun-2003
  • (2001)Communication preserving protocols for secure function evaluationProceedings of the thirty-third annual ACM symposium on Theory of computing10.1145/380752.380855(590-599)Online publication date: 6-Jul-2001
  • (2000)Communication Complexity of Functions on Direct SumsNumbers, Information and Complexity10.1007/978-1-4757-6048-4_47(589-602)Online publication date: 2000
  • (1998)Lower Bounds on the Multiparty Communication ComplexityJournal of Computer and System Sciences10.1006/jcss.1997.154756:1(90-95)Online publication date: 1-Feb-1998
  • (1992)Randomized versus nondeterministic communication complexityProceedings of the twenty-fourth annual ACM symposium on Theory of Computing10.1145/129712.129732(188-199)Online publication date: 1-Jul-1992
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