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Critique of “A Parallel Framework for Constraint-Based Bayesian Network Learning via Markov Blanket Discovery” by SCC Team From Tsinghua University | IEEE Journals & Magazine | IEEE Xplore

Critique of “A Parallel Framework for Constraint-Based Bayesian Network Learning via Markov Blanket Discovery” by SCC Team From Tsinghua University


Abstract:

Srivastava et al. propose a parallel framework to optimize Bayesian network learning in the SC20 article entitled “A Parallel Framework for Constraint-Based Bayesian Netw...Show More

Abstract:

Srivastava et al. propose a parallel framework to optimize Bayesian network learning in the SC20 article entitled “A Parallel Framework for Constraint-Based Bayesian Network Learning via Markov Blanket Discovery”. They parallelize all the phases in network constructing algorithms to achieve high performance and scalability. In this article, we reproduce the strong scaling and weak scaling experiments in that SC article. We conduct experiments on a 4-node cluster with Intel CPUs provided by the SCC committee. We further analyze the results of communication overhead. Our results show that the proposed method in that SC article scales well on the provided cluster, in accordance with the SC article.Author: Please confirm or add details for any funding or financial support for the research of this article. ?>
Published in: IEEE Transactions on Parallel and Distributed Systems ( Volume: 34, Issue: 6, June 2023)
Page(s): 1723 - 1726
Date of Publication: 26 September 2022

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References

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