On characterizing inclusion of Bayesian networks

0410745 20240103182236.220060210235959.9 1-55860-800-1 On characterizing inclusion of Bayesian networks San Francisco Morgan Kaufmann 2001 8 s. Uncertainty in Artificial Intelligence. Proceeding of the 17th Conference261-268BreeseJ.KollerD. iclusion problem dependence complex Meek's conjecture cav_un_auth*0212625 Kočka T. CZ cav_un_auth*0212862 Bouckaert R. R. NZ cav_un_auth*0101202 Studený Milan UTIA-B Department of Decision Making Theory Ústav teorie informace a automatizace AV ČR, v. v. i. 12A GA201/01/1482 GA ČR cav_un_auth*0005723 KSK1019101 GA AV ČR cav_un_auth*0000219 AV0Z1075907 The inclusion problem deals with how to characterize in graphical terms whether all independence statements in the model induced by an acyclic directed graph K are in the model induced by a second acyclic directed graph L. Several graphical characterization of inclusion are given. cav_un_auth*0212863 Uncertainty in Artificial Intelligence /17./ Seattle US 02.08.2001-05.08.2001 BA MTR http://hdl.handle.net/11104/0130833 UTIA-B 20010214 2001 2001 San Francisco Morgan Kaufmann 1-55860-800-1 Uncertainty in Artificial Intelligence. Proceeding of the 17th Conference 261 268 Breese J. 340 Koller D. 340