Experimental comparisons with respect to the usage of the promising relations in EDA-based causal discovery

DOI10.1007/S10479-016-2390-2zbMath1400.90081OpenAlexW2560061138MaRDI QIDQ1621650

Dae-Won Kim, Song Ko, Hoon Ko, Hyunki Lim

Publication date: 9 November 2018

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-016-2390-2

zbMATH Keywords

Bayesian networksefficient learningcausal discoveryestimation of distribution algorithmpromising relation

Mathematics Subject Classification ID

Stochastic network models in operations research (90B15)

Cites Work

• Hierarchical Bayesian optimization algorithm. Toward a new generation of evolutionary algorithms. With a foreword by David E. Goldberg
• A simple graphical approach for understanding probabilistic inference in Bayesian networks
• Learning Bayesian networks in the space of structures by estimation of distribution algorithms
• 10.1162/153244302760200696
• Evolutionary Computation in Combinatorial Optimization
• A survey of optimization by building and using probabilistic models
• Unnamed Item

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