A bound on the shannon capacity via a linear programming variation

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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 languageEnglish
Pages (from-to)2229-2241
Number of pages13
JournalSIAM Journal on Discrete Mathematics
Volume32
Issue number3
DOIs
StatePublished - 2018

Funding

FundersFunder number
Iowa Science Foundation
H2020 European Research Council
European Research Council
National Sleep Foundation
Alexander von Humboldt-Stiftung
Horizon 2020 Framework Programme639573
NSF-BSF2015814, 1367/14
Israel Science Foundation1030/15

    Keywords

    • Index coding
    • Linear programming
    • Shannon capacity

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