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Bibliografie

J. Cussens

  1. Haws D., Cussens J., Studený Milan :  Polyhedral approaches to learning Bayesian networks , Algebraic and Geometric Methods in Discrete Mathematics, p. 155-188 , Eds: Harrington H. A., Omar M., Wright M. [2017] DOI: 10.1090/conm/685/13751

  1. Studený Milan, Cussens J., Kratochvíl Václav :  The dual polyhedron to the chordal graph polytope and the rebuttal of the chordal graph conjecture , International Journal of Approximate Reasoning vol.138, 1 (2021), p. 188-203 [2021] Download Download DOI: 10.1016/j.ijar.2021.07.014
  2. Studený Milan, Cussens J. :  Towards using the chordal graph polytope in learning decomposable models , International Journal of Approximate Reasoning vol.88, 1 (2017), p. 259-281, 8th International Conference of Probabilistic Graphical Models, (Lugano, CH, 20160906) [2017] Download DOI: 10.1016/j.ijar.2017.06.001
  3. Cussens J., Haws D., Studený Milan :  Polyhedral aspects of score equivalence in Bayesian network structure learning , Mathematical Programming vol.164, p. 285-324 [2017] Download DOI: 10.1007/s10107-016-1087-2

  1. Studený Milan, Cussens J., Kratochvíl Václav :  Dual formulation of the chordal graph conjecture , Proceedings of Machine Learning Research, Volume 138: International Conference on Probabilistic Graphical Models, 23-25 September 2020, Hotel Comwell Rebild Bakker, Skørping, Denmark, p. 449-460 , Eds: Nielsen T. D., Jaeger M., International Conference on Probabilistic Graphical Models 2021 /10./, (Skørping, DK, 20200923) [2021] Download
  2. Studený Milan, Cussens J. :  The chordal graph polytope for learning decomposable models , Proceedings of the Eighth International Conference on Probabilistic Graphical Models, p. 499-510 , Eds: Antonucci A., Corani G., Polpo de Campos C., the Eighth International Conference on Probabilistic Graphical Models, (Lugano, CH, 06.09.2016-09.09.2016) [2016] Download DOI: 10.1016/j.ijar.2017.06.001