A bound on the shannon capacity via a linear programming variation

Sihuang Hu; Itzhak Tamo; Ofer Shayevitz

doi:10.1137/17M115565X

A bound on the shannon capacity via a linear programming variation

Sihuang Hu, Itzhak Tamo, Ofer Shayevitz

School of Electrical Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

We prove an upper bound on the Shannon capacity of a graph via a linear programming variation. We show that our bound can outperform both the Lov\'asz theta number and the Haemers minimum rank bound. As a by-product, we also obtain a new upper bound on the broadcast rate of index coding.

Original language	English
Pages (from-to)	2229-2241
Number of pages	13
Journal	SIAM Journal on Discrete Mathematics
Volume	32
Issue number	3
DOIs	https://doi.org/10.1137/17M115565X
State	Published - 2018

Keywords

Index coding
Linear programming
Shannon capacity

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10.1137/17M115565X

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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 show that our bound can outperform both the Lov\'asz theta number and the Haemers minimum rank bound. As a by-product, we also obtain a new upper bound on the broadcast rate of index coding.",

keywords = "Index coding, Linear programming, Shannon capacity",

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

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AB - We prove an upper bound on the Shannon capacity of a graph via a linear programming variation. We show that our bound can outperform both the Lov\'asz theta number and the Haemers minimum rank bound. As a by-product, we also obtain a new upper bound on the broadcast rate of index coding.

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M3 - מאמר

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JO - SIAM Journal on Discrete Mathematics

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A bound on the shannon capacity via a linear programming variation

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