Accelerating Bayesian network parameter learning using Hadoop and MapReduce

Abstract

Learning conditional probability tables of large Bayesian Networks (BNs) with hidden nodes using the Expectation Maximization algorithm is heavily computationally intensive. There are at least two bottlenecks, namely the potentially huge data set size and the requirement for computation and memory resources. This work applies the distributed computing… (More)
DOI: 10.1145/2351316.2351330

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Cite this paper

@inproceedings{Basak2012AcceleratingBN, title={Accelerating Bayesian network parameter learning using Hadoop and MapReduce}, author={Aniruddha Basak and Irina Brinster and Xianheng Ma and Ole J. Mengshoel}, booktitle={BigMine}, year={2012} }