DocumentCode
180757
Title
Exponential Separation of Information and Communication
Author
Ganor, Anat ; Kol, Gillat ; Raz, Ran
Author_Institution
Weizmann Inst. of Sci., Rehovot, Israel
fYear
2014
fDate
18-21 Oct. 2014
Firstpage
176
Lastpage
185
Abstract
We show an exponential gap between communication complexity and information complexity, by giving an explicit example for a communication task (relation), with information complexity ≤ O(k), and distributional communication complexity ≥2k. This shows that a communication protocol cannot always be compressed to its internal information. By a result of Braverman [1], our gap is the largest possible. By a result of Braverman and Rao [2], our example shows a gap between communication complexity and amortized communication complexity, implying that a tight direct sum result for distributional communication complexity cannot hold.
Keywords
communication complexity; protocols; amortized communication complexity; communication protocol; distributional communication complexity; information complexity; Complexity theory; Entropy; Games; Noise; Noise measurement; Protocols; Random variables; amortized communication complexity; communication complexity; communication compression; direct sum; information complexity;
fLanguage
English
Publisher
ieee
Conference_Titel
Foundations of Computer Science (FOCS), 2014 IEEE 55th Annual Symposium on
Conference_Location
Philadelphia, PA
ISSN
0272-5428
Type
conf
DOI
10.1109/FOCS.2014.27
Filename
6979002
Link To Document