LEADER 03923nam 22008415 450 001 9910484136303321 005 20251226203912.0 010 $a3-319-28379-0 024 7 $a10.1007/978-3-319-28379-1 035 $a(CKB)4340000000001269 035 $a(SSID)ssj0001616624 035 $a(PQKBManifestationID)16348943 035 $a(PQKBTitleCode)TC0001616624 035 $a(PQKBWorkID)14921476 035 $a(PQKB)11701364 035 $a(DE-He213)978-3-319-28379-1 035 $a(MiAaPQ)EBC5587834 035 $a(Au-PeEL)EBL5587834 035 $a(OCoLC)1066189754 035 $a(PPN)191705470 035 $a(EXLCZ)994340000000001269 100 $a20160107d2015 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aAdvanced Methodologies for Bayesian Networks $eSecond International Workshop, AMBN 2015, Yokohama, Japan, November 16-18, 2015. Proceedings /$fedited by Joe Suzuki, Maomi Ueno 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (XVIII, 265 p. 102 illus. in color.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v9505 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a3-319-28378-2 327 $aEffectiveness of graphical models including modeling. Reasoning, model selection -- Logic-probability relations -- Causality. Applying graphical models in real world settings -- Scalability -- Incremental learning.-Parallelization. 330 $aThis volume constitutes the refereed proceedings of the Second International Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2015, held in Yokohama, Japan, in November 2015. The 18 revised full papers and 6 invited abstracts presented were carefully reviewed and selected from numerous submissions. In the International Workshop on Advanced Methodologies for Bayesian Networks (AMBN), the researchers explore methodologies for enhancing the effectiveness of graphical models including modeling, reasoning, model selection, logic-probability relations, and causality. The exploration of methodologies is complemented discussions of practical considerations for applying graphical models in real world settings, covering concerns like scalability, incremental learning, parallelization, and so on. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v9505 606 $aArtificial intelligence 606 $aAlgorithms 606 $aComputer science$xMathematics 606 $aMathematical statistics 606 $aComputer science 606 $aDatabase management 606 $aApplication software 606 $aArtificial Intelligence 606 $aAlgorithms 606 $aProbability and Statistics in Computer Science 606 $aTheory of Computation 606 $aDatabase Management 606 $aComputer and Information Systems Applications 615 0$aArtificial intelligence. 615 0$aAlgorithms. 615 0$aComputer science$xMathematics. 615 0$aMathematical statistics. 615 0$aComputer science. 615 0$aDatabase management. 615 0$aApplication software. 615 14$aArtificial Intelligence. 615 24$aAlgorithms. 615 24$aProbability and Statistics in Computer Science. 615 24$aTheory of Computation. 615 24$aDatabase Management. 615 24$aComputer and Information Systems Applications. 676 $a006.3 702 $aSuzuki$b Joe$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aUeno$b Maomi$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484136303321 996 $aAdvanced Methodologies for Bayesian Networks$92831397 997 $aUNINA