Titlebook: Symbolic and Quantiative Approaches to Resoning with Uncertainty; 12th European Confer Linda C. Gaag Conference proceedings 2013 Springer-V

古代

Approximating Credal Network Inferences by Linear Programming,n be linearized by an appropriate rule for fixing all the local models apart from those of a single variable. This simple idea can be iterated and quickly leads to very accurate inferences. The approach can also be specialized to classification with credal networks based on the maximality criterion.

盘旋

冒号

偏离

CLAIM

Middle-Ear

alleviate

祖先

lanugo

A Fuzzy-Rough Data Pre-processing Approach for the Dendritic Cell Classifier,e relies on its data pre-processing phase based on the Principal Component analysis (PCA) statistical method. However, using PCA presents a limitation as it destroys the underlying semantics of the features after reduction. One possible solution to overcome this limitation was the application of Rou

NUL

Compiling Probabilistic Graphical Models Using Sentential Decision Diagrams,d context-specific independence, allowing it to scale to highly connected models that are otherwise infeasible using more traditional methods (based on treewidth alone). Previous approaches were based on performing two steps: encode a model into CNF, then compile the CNF into an equivalent but more