ML Anthology

GOBNILP: Learning Bayesian Network Structure with Integer Programming

James Cussens
PGM 2020 pp. 605-608
/pgm/2020/cussens2020pgm-gobnilp/

Abstract

The GOBNILP system for learning Bayesian networks is presented. Both the Python and C implementations are discussed. The usefulness of learning multiple BNs is highlighted. Current work on ‘pricing in’ new integer programming variables is presented.

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Cite

Text

Cussens. "GOBNILP: Learning Bayesian Network Structure with Integer Programming." Proceedings of pgm 2020, 2020.

Markdown

[Cussens. "GOBNILP: Learning Bayesian Network Structure with Integer Programming." Proceedings of pgm 2020, 2020.](https://mlanthology.org/pgm/2020/cussens2020pgm-gobnilp/)

BibTeX

@inproceedings{cussens2020pgm-gobnilp,
  title     = {{GOBNILP: Learning Bayesian Network Structure with Integer Programming}},
  author    = {Cussens, James},
  booktitle = {Proceedings of pgm 2020},
  year      = {2020},
  pages     = {605-608},
  volume    = {138},
  url       = {https://mlanthology.org/pgm/2020/cussens2020pgm-gobnilp/}
}