An effective and efficient approach for supporting the generation of synthetic memory reference traces via hierarchical hidden/non-hidden Markov Models

Alfredo Cuzzocrea, Enzo Mumolo, Marwan Hassani

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

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    Samenvatting

    This paper proposes and experimentally assesses a machine learning approach for supporting the effective and efficient generation of synthetic memory reference traces for a wide range of application scenarios. The proposed approach makes a nice use of extended hierarchical Markov models.

    Originele taal-2Engels
    TitelProceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
    UitgeverijInstitute of Electrical and Electronics Engineers
    Pagina's2953-2959
    Aantal pagina's7
    ISBN van elektronische versie9781538666500
    DOI's
    StatusGepubliceerd - 16 jan 2019
    Evenement2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC2018) - Miyazaki, Japan
    Duur: 7 okt 201810 okt 2018
    http://www.smc2018.org/

    Congres

    Congres2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC2018)
    Verkorte titelSMC2018
    LandJapan
    StadMiyazaki
    Periode7/10/1810/10/18
    Internet adres

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