LEADER 05133nam 22007695 450 001 9910299226403321 005 20200702052139.0 010 $a1-4471-6699-X 024 7 $a10.1007/978-1-4471-6699-3 035 $a(CKB)3710000000436779 035 $a(SSID)ssj0001558352 035 $a(PQKBManifestationID)16183232 035 $a(PQKBTitleCode)TC0001558352 035 $a(PQKBWorkID)14819141 035 $a(PQKB)11660275 035 $a(DE-He213)978-1-4471-6699-3 035 $a(MiAaPQ)EBC6315310 035 $a(MiAaPQ)EBC5575373 035 $a(Au-PeEL)EBL5575373 035 $a(OCoLC)911923420 035 $a(PPN)186400446 035 $a(EXLCZ)993710000000436779 100 $a20150619d2015 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aProbabilistic Graphical Models$b[electronic resource] $ePrinciples and Applications /$fby Luis Enrique Sucar 205 $a1st ed. 2015. 210 1$aLondon :$cSpringer London :$cImprint: Springer,$d2015. 215 $a1 recurso en línea (xxiv, 253 páginas) 225 1 $aAdvances in Computer Vision and Pattern Recognition,$x2191-6586 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a1-4471-6698-1 327 $aPart I: Fundamentals -- Introduction -- Probability Theory -- Graph Theory -- Part II: Probabilistic Models -- Bayesian Classifiers -- Hidden Markov Models -- Markov Random Fields -- Bayesian Networks: Representation and Inference -- Bayesian Networks: Learning -- Dynamic and Temporal Bayesian Networks -- Part III: Decision Models -- Decision Graphs -- Markov Decision Processes -- Part IV: Relational and Causal Models -- Relational Probabilistic Graphical Models -- Graphical Causal Models. 330 $aThis accessible text/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. The book covers the fundamentals for each of the main classes of PGMs, including representation, inference and learning principles, and reviews real-world applications for each type of model. These applications are drawn from a broad range of disciplines, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, influence diagrams, and Markov decision processes. Topics and features: Presents a unified framework encompassing all of the main classes of PGMs Explores the fundamental aspects of representation, inference and learning for each technique Describes the practical application of the different techniques Examines the latest developments in the field, covering multidimensional Bayesian classifiers, relational graphical models and causal models Provides exercises, suggestions for further reading, and ideas for research or programming projects at the end of each chapter Suggests possible course outlines for instructors in the preface This classroom-tested work is suitable as a textbook for an advanced undergraduate or a graduate course in probabilistic graphical models for students of computer science, engineering, and physics. Professionals wishing to apply probabilistic graphical models in their own field, or interested in the basis of these techniques, will also find the book to be an invaluable reference. Dr. Luis Enrique Sucar is a Senior Research Scientist at the National Institute for Astrophysics, Optics and Electronics (INAOE), Puebla, Mexico. 410 0$aAdvances in Computer Vision and Pattern Recognition,$x2191-6586 606 $aMathematical statistics 606 $aArtificial intelligence 606 $aPattern recognition 606 $aProbabilities 606 $aElectrical engineering 606 $aProbability and Statistics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17036 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aProbability Theory and Stochastic Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/M27004 606 $aElectrical Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T24000 615 0$aMathematical statistics. 615 0$aArtificial intelligence. 615 0$aPattern recognition. 615 0$aProbabilities. 615 0$aElectrical engineering. 615 14$aProbability and Statistics in Computer Science. 615 24$aArtificial Intelligence. 615 24$aPattern Recognition. 615 24$aProbability Theory and Stochastic Processes. 615 24$aElectrical Engineering. 676 $a004 700 $aSucar$b Luis Enrique$4aut$4http://id.loc.gov/vocabulary/relators/aut$01060261 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299226403321 996 $aProbabilistic Graphical Models$92512048 997 $aUNINA LEADER 01541oam 2200469 450 001 9910704892703321 005 20130830140322.0 035 $a(CKB)5470000002444804 035 $a(OCoLC)624409341$z(OCoLC)679986379 035 $a(EXLCZ)995470000002444804 100 $a20100521d1988 ua 0 101 0 $aeng 135 $aurbn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aHardwood trade trends $eU.S. exports /$fWilliam G. Luppold, Philip A. Araman 210 1$aBroomall, PA :$cUnited States Department of Agriculture, Forest Service, Northeastern Forest Experiment Station,$d[1988] 215 $a1 online resource (8 pages) $cillustrations 225 1 $aResearch paper NE ;$v611 300 $aTitle from title screen (viewed Aug. 30, 2013). 300 $a"February 1988." 320 $aIncludes bibliographical references (page 8). 517 $aHardwood trade trends 606 $aSupply and demand 606 $aHardwoods$zUnited States$xMarketing 606 $aExports$zUnited States 615 0$aSupply and demand. 615 0$aHardwoods$xMarketing. 615 0$aExports 700 $aLuppold$b William G.$01393659 702 $aAraman$b Philip A. 712 02$aNortheastern Forest Experiment Station (Radnor, Pa.), 801 0$bOCLCE 801 1$bOCLCE 801 2$bOCLCQ 801 2$bOCLCA 801 2$bGPO 906 $aBOOK 912 $a9910704892703321 996 $aHardwood trade trends$93462132 997 $aUNINA LEADER 02248nam 2200493 450 001 9910789671203321 005 20230721014321.0 010 $a1-283-20202-6 010 $a9786613202024 010 $a0-8264-4279-X 035 $a(CKB)2670000000106655 035 $a(EBL)742664 035 $a(OCoLC)741690823 035 $a(MiAaPQ)EBC5309742 035 $a(MiAaPQ)EBC742664 035 $a(Au-PeEL)EBL742664 035 $a(CaONFJC)MIL320202 035 $a(EXLCZ)992670000000106655 100 $a20180316h20072003 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aPopular magic $ecunning folk in English history /$fOwen Davies 210 1$aLondon, England ;$aNew York, New York :$cHambledon Continuum,$d2007. 210 4$d©2003 215 $a1 online resource (263 p.) 300 $aOriginally published: as Cunning-folk. London: Hambledon and London, 2003. 311 $a1-84725-036-X 320 $aIncludes bibliographical references and index. 327 $aContents; Introduction; Acknowledgements; 1 Cunning-Folk and the Law; 2 For Good or Evil?; 3 Who and Why; 4 Services; 5 Books; 6 Written Charms; 7 European Comparisons; 8 Cunning-Folk in the Twentieth Century; Notes; Bibliography; Index 330 $aCunning-folk were local practitioners of magic, providing small-scale but valued service to the community. They were far more representative of magical practice than the arcane delvings of astrologers and necromancers. Mostly unsensational in their approach, cunning-folk helped people with everyday problems: how to find lost objects; how to escape from bad luck or a suspected spell; and how to attract a lover or keep the love of a husband or wife. While cunning-folk sometimes fell foul of the authorities, both church and state often turned a blind eye to their existence and practices, distingu 606 $aMagic$zEngland$xHistory 615 0$aMagic$xHistory. 676 $a133.430942 700 $aDavies$b Owen$f1969-$0800733 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910789671203321 996 $aPopular magic$93704339 997 $aUNINA LEADER 01647nam 2200445 450 001 9910792616603321 005 20180227110943.0 010 $a1-4985-4034-1 035 $a(CKB)3710000001045013 035 $a(MiAaPQ)EBC4799344 035 $a(EXLCZ)993710000001045013 100 $a20170216h20172017 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aContemporary anti-muslim politics $eaggressions and exclusions /$fKenneth J. Long 210 1$aLanham, [Maryland] :$cLexington Books,$d2017. 210 4$d©2017 215 $a1 online resource (171 pages) 311 $a1-4985-4035-X 311 $a1-4985-4033-3 320 $aIncludes bibliographical references and index. 327 $aMauthausen -- Paris -- Muslimfeindlichkeit -- What is a Muslim? -- Huntington -- Stereotypes -- Imperialism -- Arab spring -- Tolerance, secularism and cultural pluralism -- Cartoons and sacrilege -- Misrepresentations for the non-represented -- Limited democracy and questionable convictions. 606 $aInternational relations 606 $aInternational relations$y20th century 607 $aWestern countries$xRelations$zIslamic countries 607 $aIslamic Countries$xRelations$xz Western countries 615 0$aInternational relations. 615 0$aInternational relations 676 $a327 700 $aLong$b Kenneth J. $01490213 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910792616603321 996 $aContemporary anti-muslim politics$93711463 997 $aUNINA