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Induced Semantics for Undirected Graphs: Another Look at the Hammersley-Clifford Theorem

机译:对无向图的诱发语义:另一点看哈默利 - 克利福德定理

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The Hammersley-Clifford (H-C) theorem relates the factorization properties of a probability distribution to the clique structure of an undirected graph. If a density factorizes according to the clique structure of an undirected graph, the theorem guarantees that the distribution satisfies the Markov property and vice versa. We show how to generalize the H-C theorem to different notions of decomposability and the corresponding generalized-Markov property. Finally we discuss how our technique might be used to arrive at other generalizations of the H-C theorem, inducing a graph semantics adapted to the modeling problem.
机译:Hammersley-Clifford(H-C)定理将概率分布的分解性属性涉及到一个无向图的Clique结构的分解性。如果根据无向图的Clique结构的密度分解,则定理保证分布满足马尔可夫属性,反之亦然。我们展示了如何将H-C定理概括为不同的分解概念和相应的广义 - 马尔可夫属性。最后,我们讨论了我们的技术如何用于到达H-C定理的其他概括,诱导适于建模问题的图形语义。

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