Isbn: 9786131834080 - markov logic network: probabilistic logic, markov random field, satisfiability, entailment, first-order logic, well-formed formula, real number, logical connective (3 risultati)

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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 64 pp. Englisch.

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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. A Markov logicnetwork (or MLN) is a probabilistic logic which applies the ideas of aMarkov network to first-order logic. Markov logic networks generalizefirst-order logic, in the sense that, in a certain limit, allunsatisfiable statements have a probability of zero, and the set of allentailed formulas have probability one. Briefly, it is a collection offormulas from first order logic, to each of which is assigned a realnumber, the weight. Taken as a Markov network, the vertices of thenetwork graph are atomic formulas, and the edges are the logicalconnectives used to construct the formula. Each formula is considered tobe a clique, and the Markov blanket is the set of formulas in which agiven atom appears. A potential function is associated to each formulaand takes the value of one when the formula is true, and zero when it isfalse. The potential function is combined with the weight to form theGibbs measure and partition function for the Markov network.…

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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. A Markov logicnetwork (or MLN) is a probabilistic logic which applies the ideas of aMarkov network to first-order logic. Markov logic networks generalizefirst-order logic, in the sense that, in a certain limit, allunsatisfiable statements have a probability of zero, and the set of allentailed formulas have probability one. Briefly, it is a collection offormulas from first order logic, to each of which is assigned a realnumber, the weight. Taken as a Markov network, the vertices of thenetwork graph are atomic formulas, and the edges are the logicalconnectives used to construct the formula. Each formula is considered tobe a clique, and the Markov blanket is the set of formulas in which agiven atom appears. A potential function is associated to each formulaand takes the value of one when the formula is true, and zero when it isfalse. The potential function is combined with the weight to form theGibbs measure and partition function for the Markov network.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.…