
Dependence and Relevance: A probabilistic view
We examine three probabilistic concepts related to the sentence "two var...
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Between steps: Intermediate relaxations between bigM and convex hull formulations
This work develops a class of relaxations in between the bigM and conve...
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Binary extended formulations and sequential convexification
A binarization of a bounded variable x is a linear formulation with vari...
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An Algorithm for Computing Probabilistic Propositions
A method for computing probabilistic propositions is presented. It assum...
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A Theory of Slicing for Probabilistic ControlFlow Graphs
We present a theory for slicing probabilistic imperative programs  con...
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Two generalizations of Markov blankets
In a probabilistic graphical model on a set of variables V, the Markov b...
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Optimization of Tree Ensembles
Tree ensemble models such as random forests and boosted trees are among ...
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Separable and transitive graphoids
We examine three probabilistic formulations of the sentence a and b are totally unrelated with respect to a given set of variables U. First, two variables a and b are totally independent if they are independent given any value of any subset of the variables in U. Second, two variables are totally uncoupled if U can be partitioned into two marginally independent sets containing a and b respectively. Third, two variables are totally disconnected if the corresponding nodes are disconnected in every belief network representation. We explore the relationship between these three formulations of unrelatedness and explain their relevance to the process of acquiring probabilistic knowledge from human experts.
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