F. G. Cozman. Irrelevance and independence relations in Quasi-Bayesian networks. In Proceedings UAI-98, pp. 89--96. Morgan Kaufmann, 1998. Home/Search Document Details and Download
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Credal Networks under Maximum Entropy - Lukasiewicz (2000) (Correct)
.... in the Bayesian network framework are especially discussed by Breese and Fertig [2] Tessem [36] Thone et al. 37] and Zaffalon [12] Bayesian networks with local convex sets of conditional distributions, called credal networks (or also QuasiBayesian networks) are especially analyzed by Cozman [7, 8]. One philosophy to handle credal networks is to insist on working with sets of probability distributions. In this case, an agent follows a very cautious path by considering every distribution as relevant. But this also means that there might be ambiguous situations in which the agent simply does ....
....detail in the appendix. INFSYS RR 1843 00 03 2 TECHNICAL PRELIMINARIES In this section, we describe the technical background. 2. 1 CREDAL NETWORKS We now give a brief introduction to Bayesian networks, interval Bayesian networks, and credal networks (see especially [30] 36, 37, 12] and [7, 8], respectively) A Bayesian network is defined by a directed acyclic graph D over discrete random variables X 1 ; X 2 ; X n as nodes and by a conditional probability distribution Pr(X i j pa(X i ) for each variable X i and each instantiation pa(X i ) of its parents pa(X i ) It specifies ....
[Article contains additional citation context not shown here]
F. G. Cozman. Irrelevance and independence relations in Quasi-Bayesian networks. In Proceedings UAI-98, pp. 89--96. Morgan Kaufmann, 1998.
Credal Networks under Maximum Entropy - Lukasiewicz (2000) (Correct)
.... in the Bayesian network framework are especially discussed by Breese and Fertig [2] Tessem [37] Thone et al. 38] and Zaffalon [12] Bayesian networks with local convex sets of conditional distributions, called credal networks (or also Quasi Bayesian networks) are especially analyzed by Cozman [7, 8]. One philosophy to handle credal networks is to insist on working with sets of probability distributions. In this case, an agent follows a very cautious path by considering every distribution as relevant. But this also means that there might be ambiguous situations in which the agent simply does ....
....that all proofs are given in full detail in [24] 2 TECHNICAL PRELIMINARIES In this section, we describe the technical background. 2. 1 CREDAL NETWORKS We now give a brief introduction to Bayesian networks, interval Bayesian networks, and credal networks (see especially [31] 37, 38, 12] and [7, 8], respectively) A Bayesian network is defined by a directed acyclic graph D over discrete random variables X 1 ; X 2 ; Xn as nodes and by a conditional probability distribution Pr(X i j pa(X i ) for each variable X i and each instantiation pa(X i ) of its parents pa(X i ) It specifies ....
[Article contains additional citation context not shown here]
F. G. Cozman. Irrelevance and independence relations in Quasi-Bayesian networks. In Proceedings UAI-98, pp. 89-- 96. Morgan Kaufmann, 1998.
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