A bound on the shannon capacity via a linear programming variation

Sihuang Hu; Itzhak Tamo; Ofer Shayevitz

doi:10.1109/ISIT.2017.8006691

A bound on the shannon capacity via a linear programming variation

Sihuang Hu, Itzhak Tamo, Ofer Shayevitz

School of Electrical Engineering

Tel Aviv University

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

Abstract

We prove an upper bound on the Shannon capacity of a graph via a linear programming variation. We also show that our bound can be better than Lovász theta number and Haemers minimum rank bound.

Original language	English
Title of host publication	2017 IEEE International Symposium on Information Theory, ISIT 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1063-1066
Number of pages	4
ISBN (Electronic)	9781509040964
DOIs	https://doi.org/10.1109/ISIT.2017.8006691
State	Published - 9 Aug 2017
Event	2017 IEEE International Symposium on Information Theory, ISIT 2017 - Aachen, Germany Duration: 25 Jun 2017 → 30 Jun 2017

Publication series

Name	IEEE International Symposium on Information Theory - Proceedings
ISSN (Print)	2157-8095

Conference

Conference	2017 IEEE International Symposium on Information Theory, ISIT 2017
Country/Territory	Germany
City	Aachen
Period	25/06/17 → 30/06/17

Funding

Funders	Funder number
Iowa Science Foundation
H2020 European Research Council
European Research Council
National Sleep Foundation
Alexander von Humboldt-Stiftung
Horizon 2020 Framework Programme	639573
NSF-BSF	2015814, 1367/14
Israel Science Foundation	1030/15

Access to Document

10.1109/ISIT.2017.8006691

Cite this

Hu, S., Tamo, I., & Shayevitz, O. (2017). A bound on the shannon capacity via a linear programming variation. In 2017 IEEE International Symposium on Information Theory, ISIT 2017 (pp. 1063-1066). Article 8006691 (IEEE International Symposium on Information Theory - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2017.8006691

@inproceedings{b36393b5c1d94228b8ca1f877b955f3a,

title = "A bound on the shannon capacity via a linear programming variation",

abstract = "We prove an upper bound on the Shannon capacity of a graph via a linear programming variation. We also show that our bound can be better than Lov{\'a}sz theta number and Haemers minimum rank bound.",

author = "Sihuang Hu and Itzhak Tamo and Ofer Shayevitz",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Symposium on Information Theory, ISIT 2017 ; Conference date: 25-06-2017 Through 30-06-2017",

year = "2017",

month = aug,

day = "9",

doi = "10.1109/ISIT.2017.8006691",

language = "אנגלית",

series = "IEEE International Symposium on Information Theory - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1063--1066",

booktitle = "2017 IEEE International Symposium on Information Theory, ISIT 2017",

address = "ארצות הברית",

}

Hu, S, Tamo, I & Shayevitz, O 2017, A bound on the shannon capacity via a linear programming variation. in 2017 IEEE International Symposium on Information Theory, ISIT 2017., 8006691, IEEE International Symposium on Information Theory - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 1063-1066, 2017 IEEE International Symposium on Information Theory, ISIT 2017, Aachen, Germany, 25/06/17. https://doi.org/10.1109/ISIT.2017.8006691

A bound on the shannon capacity via a linear programming variation. / Hu, Sihuang; Tamo, Itzhak ; Shayevitz, Ofer.
2017 IEEE International Symposium on Information Theory, ISIT 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1063-1066 8006691 (IEEE International Symposium on Information Theory - Proceedings).

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

TY - GEN

T1 - A bound on the shannon capacity via a linear programming variation

AU - Hu, Sihuang

AU - Tamo, Itzhak

AU - Shayevitz, Ofer

PY - 2017/8/9

Y1 - 2017/8/9

N2 - We prove an upper bound on the Shannon capacity of a graph via a linear programming variation. We also show that our bound can be better than Lovász theta number and Haemers minimum rank bound.

AB - We prove an upper bound on the Shannon capacity of a graph via a linear programming variation. We also show that our bound can be better than Lovász theta number and Haemers minimum rank bound.

UR - http://www.scopus.com/inward/record.url?scp=85034056893&partnerID=8YFLogxK

U2 - 10.1109/ISIT.2017.8006691

DO - 10.1109/ISIT.2017.8006691

M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???

AN - SCOPUS:85034056893

T3 - IEEE International Symposium on Information Theory - Proceedings

SP - 1063

EP - 1066

BT - 2017 IEEE International Symposium on Information Theory, ISIT 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 IEEE International Symposium on Information Theory, ISIT 2017

Y2 - 25 June 2017 through 30 June 2017

ER -

A bound on the shannon capacity via a linear programming variation

Abstract

Publication series

Conference

Funding

Access to Document

Other files and links

Fingerprint

Cite this