D. Haws

  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. 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
  2. Studený Milan, Haws D. :  Learning Bayesian network structure: towards the essential graph by integer linear programming tools , International Journal of Approximate Reasoning vol.55, 4 (2014), p. 1043-1071 [2014] Download DOI: 10.1016/j.ijar.2013.09.016

  1. Studený Milan, Haws D., Hemmecke R., Lindner S. :  Polyhedral approach to statistical learning graphical models , Harmony of Gröbner Bases and the Modern Industrial Society, p. 346-372, The 2nd CREST-SBM International Conference "Harmony of Groebner Bases and the Modern Industrial Society", (Osaka, JP, 28.06.2012-2.07.2012) [2012] Download DOI: 10.1142/9789814383462_0020
  2. Studený Milan, Haws D. :  On polyhedral approximations of polytopes for learning Bayes nets, ÚTIA AV ČR, (Praha 2011) Research Report 2303 [2011] Download