An Introduction to Bayesian Network Theory and Usage
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We define the crossing number for an embedding of a graph G into R^3, and prove a lower bound on it which almost implies the classical crossing lemma. We also give sharp bounds on the space crossing numbers of pseudo-random graphs. ...
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We consider the transductive learning problem when the labels belong to a continuous space. Through the use of spectral graph wavelets, we explore the benefits of multiresolution analysis on a graph constructed from the labeled and unlabeled data. The spec ...
Due to the appearance of data on networks such as internet or Facebook, the number of applications of signal on weighted graph is increasing. Unfortunately, because of the irregular structure of this data, classical signal processing techniques are not app ...
In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of cont ...
Navigation of a group of autonomous agents that are required to maintain a formation is a challenging task which has not been studied much especially in 3-D terrains. This paper presents a novel approach to collision free path finding of multiple agents pr ...
In conventional group testing, the goal is to detect a small subset of defecting items D in a large population N by grouping \textit{arbitrary} subset of N into different pools. The result of each group test $\mathcal{T} ...
Research on automatic recognition of named entities from Arabic text uses techniques that work well for the Latin based languages such as local grammars, statistical learning models, pattern matching, and rule-based techniques. These techniques boost their ...
