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» DisNet: A Framework for Distributed Graph Computation
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IPPS
2009
IEEE
15 years 4 months ago
Compact graph representations and parallel connectivity algorithms for massive dynamic network analysis
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication t...
Kamesh Madduri, David A. Bader
ECCV
2006
Springer
15 years 11 months ago
Statistical Priors for Efficient Combinatorial Optimization Via Graph Cuts
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Daniel Cremers, Leo Grady
GECCO
2007
Springer
201views Optimization» more  GECCO 2007»
15 years 3 months ago
A parallel framework for loopy belief propagation
There are many innovative proposals introduced in the literature under the evolutionary computation field, from which estimation of distribution algorithms (EDAs) is one of them....
Alexander Mendiburu, Roberto Santana, Jose Antonio...
IEEEPACT
2002
IEEE
15 years 2 months ago
A Framework for Parallelizing Load/Stores on Embedded Processors
Many modern embedded processors (esp. DSPs) support partitioned memory banks (also called X-Y memory or dual bank memory) along with parallel load/store instructions to achieve co...
Xiaotong Zhuang, Santosh Pande, John S. Greenland ...
CISS
2008
IEEE
15 years 3 months ago
Distributed estimation in wireless sensor networks via variational message passing
Abstract – In this paper, a variational message passing framework is proposed for Markov random fields. Analogous to the traditional belief propagation algorithm, variational mes...
Yanbing Zhang, Huaiyu Dai