We introduce the problem of identifying representative nodes in probabilistic graphs, motivated by the need to produce different simple views to large networks. We define a probabilistic similarity measure for nodes, and then apply clustering methods to find groups of nodes. Finally, a representative is output from each cluster. We report on experiments with real biomedical data, using both the...

We propose a distributed connectivity maintenance protocol that explicitly accounts for the probabilistic nature of wireless communication links. The proposed protocol is simple to implement and it achieves a given target communication quality between nodes, which is quantified by the minimum packet delivery rate between any pair of nodes in the network. We demonstrate the robustness of the pro...

We show a hybrid probabilistic and possibilistic model for assessing the risk of a service level agreement for a computing task in a cluster/grid environment. Using the predictive probabilistic approach we develop a framework for resource management in grid computing, and by introducing an upper limit for the number of failures we approximate the probability that a particular computing task is ...

The probabilistic graphs framework models the uncertainty inherent in real-world domains by means of probabilistic edges whose value quantifies the likelihood of the edge existence or the strength of the link it represents. The goal of this paper is to provide a learning method to compute the most likely relationship between two nodes in a framework based on probabilistic graphs. In particular,...

Fault localization is an important and expensive task in software debugging. Some probabilistic graphical models such as probabilistic program dependence graph (PPDG) have been used in fault localization. However, PPDG is insufficient to reason across nonadjacent nodes and only support making inference about local anomaly. In this paper, we propose a novel probabilistic graphical model called B...

a reliability analysis of suspension bridges against buffeting failure due to gustiness of wind velocity is carried out using the concept of pra (probabilistic risk analysis) procedure. for this purpose, the bending stresses at the critical nodes of the bridge deck are obtained for buffeting forces using a spectral analysis technique and a finite element approach. for the purpose of reliability...

We present a version of the CCP paradigm, which is both distributed and probabilistic. We consider networks with a fixed number of nodes, each of them possessing a local and independent constraint store. While locally the computations evolve asynchronously, following the usual rules of (probabilistic) CCP, the communications among different nodes are synchronous. There are channels, and through...

Proposed method, called Probabilistic Nodes Combination (PNC), is the method of 2D curve modeling and handwriting identification by using the set of key points. Nodes are treated as characteristic points of signature or handwriting for modeling and writer recognition. Identification of handwritten letters or symbols need modeling and the model of each individual symbol or character is built by ...

Qualitative probabilistic reasoning in a Bayesian network often reveals tradeoos: relationships that are ambiguous due to competing qualitative innuences. We present two techniques that combine qualitative and numeric probabilistic reasoning to resolve such tradeoos, inferring the qualitative relationship between nodes in a Bayesian network. The rst approach incrementally marginalizes nodes in ...