An orientation of an undirected graph G is assignment exactly one direction to each edge . Converting two-way traffic networks one-way and bidirectional communication unidirectional are practical instances orientations. In these contexts minimising the diameter resulting oriented prime interest. The n -star network topology was proposed as alternative hypercube for multiprocessor systems by Ake...

We present a unified graphical model framework for describing compound codes and deriving iterative decoding algorithms. After reviewing a variety of graphical models (Markov random fields, Tanner graphs, and Bayesian networks), we derive a general distributed marginalization algorithm for functions described by factor graphs. From this general algorithm, Pearl’s belief propagation algorithm is...

We present a new support vector machine (SVM) algorithm and graphical methods for mining very large datasets. We develop the active selection of training data points that can significantly reduce the training set in the SVM classification. We summarize the massive datasets into interval data. We adapt the RBF kernel used by the SVM algorithm to deal with this interval data. We only keep the dat...

We present a new support vector machine (SVM) algorithm and graphical methods for mining very large datasets. We develop the active selection of training data points that can significantly reduce the training set in the SVM classification. We summarize the massive datasets into interval data. We adapt the RBF kernel used by the SVM algorithm to deal with this interval data. We only keep the dat...

We consider the problem of computing r-th order statistics, namely finding an assignment having rank r in a probabilistic graphical model. We show that this problem is NP-hard even when the graphical model has no edges (zero-treewidth models) via a reduction from the number partitioning problem. We use this reduction, specifically pseudopolynomial time algorithms for number partitioning, to yie...

We propose a new localized inference algorithm for answering marginalization queries in large graphical models with the correlation decay property. Given a query variable and a large graphical model, we define a much smaller model in a local region around the query variable in the target model so that the marginal distribution of the query variable can be accurately approximated. We introduce t...

This paper introduces graphical models as a natural environment in which to formulate and solve problems in genetics and related areas. Particular emphasis is given to the relationships among various local computation algorithms which have been developed within the hitherto mostly separate areas of graphical models and genetics. The potential of graphical models is explored and illustrated thro...

SUMMARY We propose SW#, a new CUDA graphical processor unit-enabled and memory-efficient implementation of dynamic programming algorithm, for local alignment. It can be used as either a stand-alone application or a library. Although there are other graphical processor unit implementations of the Smith-Waterman algorithm, SW# is the only one publicly available that can produce sequence alignment...