Titlebook: Symbolic and Quantitative Approaches to Reasoning with Uncertainty; 7th European Confere Thomas Dyhre Nielsen,Nevin Lianwen Zhang Conferenc

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Dynamic Importance Sampling Computation in Bayesian Networkss quality and so reducing the variance of the future weights. The paper shows that this can be done with little computational effort. The experiments carried out show that the final results can be very good even in the case that the initial sampling distribution is far away from the optimum.

collagen

Introducing Situational Influences in QPNsof the network. We show that reasoning with such situational influences may forestall ambiguous results upon inference; we further show how these influences change as the current state of the network changes.

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Acetabulum

Approximating Conditional MTE Distributions by Means of Mixed Treesnditional MTE densities using mixed trees, which are graphical structures similar to classification trees. Criteria for selecting the variables during the construction of the tree and for pruning the leaves are defined in terms of the mean square error and entropy-like measures.

娘娘腔

Qualitative Decision Rules under Uncertaintyut that two main approaches exist according to whether degrees of uncertainty and degrees of utility are commensurate (that is, belong to a unique scale) or not. Savage-like axiomatics for both approaches are surveyed. In such a framework, acts are functions from states to results, and decision rule

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A Representation Theorem and Applicationshe only ones that preserve certain elementary probabilistic relationships. This result provides a new perspective on a variety of probabilistic inference problems in which invariance considerations play a role. Two particular applications we consider in this paper are the development of an equivaria

彻底明白

A Multi-layered Bayesian Network Model for Structured Document Retrievals to index, retrieve and present documents according to the given document structure. The paper presents the design of an Information Retrieval system for multimedia structured documents, like for example journal articles, e-books, and MPEG-7 videos. The system is based on Bayesian Networks, since t

Interstellar

Using Kappas as Indicators of Strength in Qualitative Probabilistic Networkss, but do not provide for indicating the strengths of these influences. As a result, trade-offs between conflicting influences remain unresolved upon inference. In this paper, we investigate the use of order-of-magnitude kappa values to capture strengths of influences in a qualitative network. We de

BACLE

Qualitative Bayesian Networks with Logical Constraintsls involving logical constraints among the given variables. The aim of this paper is to show how this theory can be extended in such a way to represent also the logical constraints in the graph through an enhanced version of Qualitative Bayesian Networks. The relative algorithm for building these gr