Abstract
In this paper, we firstly formulate the concept of “ordering of sets” to represent the relationships between classes of variables. And then a parallel algorithm with little inter-processors communication is proposed based on “ordering of sets”. In our algorithm, the search space is partitioned in an effective way and be distributed to multi-processors to be searched in parallel. The results of experiments show that, compared with traditional greedy DAG search algorithm, our algorithm is more effective, especially for large domains.
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References
Du, T., Zhang, S.S., Wang, Z.: Structure Learning Based on Ordering of Sets, accepted by IEEE CIT 2005 (2005)
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Du, T., Zhang, S.S., Wang, Z. (2005). Parallel Learning of Bayesian Networks Based on Ordering of Sets. In: Grumbach, S., Sui, L., Vianu, V. (eds) Advances in Computer Science – ASIAN 2005. Data Management on the Web. ASIAN 2005. Lecture Notes in Computer Science, vol 3818. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596370_33
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DOI: https://doi.org/10.1007/11596370_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30767-9
Online ISBN: 978-3-540-32249-8
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