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LP relaxations and pruning for characteristic imsets

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    0377918 - ÚTIA 2013 CZ eng V - Research Report
    Studený, Milan
    LP relaxations and pruning for characteristic imsets.
    Praha: ÚTIA AVČR, 2012. 30 s. Research Report, 2323.
    R&D Projects: GA ČR GA201/08/0539
    Institutional support: RVO:67985556
    Keywords : learning Bayesian network structure * quality criterion * integer linear programming
    Subject RIV: BA - General Mathematics
    http://library.utia.cas.cz/separaty/2012/MTR/Studeny-LP relaxations and pruning for characteristic imsets.pdf

    The geometric approach to learning BN structure is to represent it by a certain vector; a suitable such zero-one vector is the characteristic imset, which allows to reformulate the task of finding global maximum of a score over BN structures as an integer linear programming problem. The main contribution of this report is an LP relaxation of the corresponding polytope, that is, a polyhedral description of the domain of the respective integer linear programming problem.
    Permanent Link: http://hdl.handle.net/11104/0209940

     
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