MARC Record from marc_columbia

LEADER: 07220cam a2200997 a 4500
001 9254242
005 20220730225317.0
006 m o d
007 cr cnu---unuuu
008 070925s2007 maua ob 001 0 eng d
035 $a(OCoLC)ocn173281492
035 $a(NNC)9254242
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020 $a9780262255691$q(electronic bk.)
020 $a0262255693$q(electronic bk.)
020 $a9781429499170$q(electronic bk.)
020 $a1429499176$q(electronic bk.)
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020 $a9780262528047$q(print)
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020 $z0262026171$q(alk. paper)
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037 $a7443$bMIT Press
037 $a9780262255691$bMIT Press
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050 4 $aQ325.5$b.P74 2007eb
072 7 $aCOM$x005030$2bisacsh
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049 $aZCUA
245 00 $aPredicting structured data /$cedited by Gökhan Bakır [and others].
260 $aCambridge, Mass. :$bMIT Press,$c©2007.
300 $a1 online resource (viii, 348 pages) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
490 1 $aAdvances in neural information processing systems
500 $aCollected papers based on talks presented at two Neural Information Processing Systems workshops.
504 $aIncludes bibliographical references (pages 319-340) and index.
505 0 $aMeasuring Similarity with Kernels -- Discriminative Models -- Modeling Structure via Graphical Models -- Joint Kernel Maps / Jason Weston [and others] -- Support Vector Machine Learning for Interdependent and Structured Output Spaces / Yasemin Altun, Thomas Hofmann, and Ioannis Tsochandiridis -- Efficient Algorithms for Max-Margin Structured Classification / Juho Rousu [and others] -- Discriminative Learning of Prediction Suffix Trees with the Perceptron Algorithm / Ofer Dekel, Shai Shalev-Shwartz, and Yoram Singer -- A General Regression Framework for Learning String-to-String Mappings / Corinna Cortes, Mehryar Mohri, and Jason Weston -- Learning as Search Optimization / Hal Daume III and Daniel Marcu -- Energy-Based Models / Yann LeCun [and others] -- Generalization Bounds and Consistency for Structured Labeling / David McAllester -- Kernel Conditional Graphical Models / Fernando Perez-Cruz, Zoubin Ghahramani, and Massimiliano Pontil -- Density Estimation of Structured Outputs in Reproducing Kernel Hilbert Spaces / Yasemin Altun and Alex J. Smola -- Gaussian Process Belief Propagation / Matthias W. Seeger.
506 $3Use copy$fRestrictions unspecified$2star$5MiAaHDL
533 $aElectronic reproduction.$b[Place of publication not identified] :$cHathiTrust Digital Library,$d2010.$5MiAaHDL
538 $aMaster and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.$uhttp://purl.oclc.org/DLF/benchrepro0212$5MiAaHDL
583 1 $adigitized$c2010$hHathiTrust Digital Library$lcommitted to preserve$2pda$5MiAaHDL
588 0 $aPrint version record.
546 $aEnglish.
520 $aState-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure. Machine learning develops intelligent computer systems that are able to generalize from previously seen examples. A new domain of machine learning, in which the prediction must satisfy the additional constraints found in structured data, poses one of machine learning's greatest challenges: learning functional dependencies between arbitrary input and output domains. This volume presents and analyzes the state of the art in machine learning algorithms and theory in this novel field. The contributors discuss applications as diverse as machine translation, document markup, computational biology, and information extraction, among others, providing a timely overview of an exciting field. Contributors Yasemin Altun, Gokhan Bakir, Olivier Bousquet, Sumit Chopra, Corinna Cortes, Hal Daume III, Ofer Dekel, Zoubin Ghahramani, Raia Hadsell, Thomas Hofmann, Fu Jie Huang, Yann LeCun, Tobias Mann, Daniel Marcu, David McAllester, Mehryar Mohri, William Stafford Noble, Fernando Perez-Cruz, Massimiliano Pontil, Marc'Aurelio Ranzato, Juho Rousu, Craig Saunders, Bernhard Scholkopf, Matthias W. Seeger, Shai Shalev-Shwartz, John Shawe-Taylor, Yoram Singer, Alexander J. Smola, Sandor Szedmak, Ben Taskar, Ioannis Tsochantaridis, S.V.N Vishwanathan, Jason Weston
650 0 $aMachine learning.
650 0 $aComputer algorithms.
650 0 $aKernel functions.
650 0 $aData structures (Computer science)
650 0 $aAlgorithms.
650 2 $aAlgorithms
650 6 $aApprentissage automatique.
650 6 $aAlgorithmes.
650 6 $aNoyaux (Mathématiques)
650 6 $aStructures de données (Informatique)
650 7 $aalgorithms.$2aat
650 7 $aCOMPUTERS$xEnterprise Applications$xBusiness Intelligence Tools.$2bisacsh
650 7 $aCOMPUTERS$xIntelligence (AI) & Semantics.$2bisacsh
650 7 $aAlgorithms.$2fast$0(OCoLC)fst00805020
650 7 $aComputer algorithms.$2fast$0(OCoLC)fst00872010
650 7 $aData structures (Computer science)$2fast$0(OCoLC)fst00887978
650 7 $aKernel functions.$2fast$0(OCoLC)fst00986892
650 7 $aMachine learning.$2fast$0(OCoLC)fst01004795
650 7 $aLernen$x(Informatik)$xKernel (Informatik)$2idsbb
650 7 $aLernen$x(Informatik)$xStrukturlogik.$2idsbb
650 7 $aStrukturlogik$xLernen (Informatik)$2idsbb
650 7 $aKernel$x(Informatik)$xLernen (Informatik)$2idsbb
653 $aCOMPUTER SCIENCE/Machine Learning & Neural Networks
655 0 $aElectronic books.
655 4 $aElectronic books.
700 1 $aBakIr, Gökhan.
710 2 $aNeural Information Processing Systems Foundation.
776 08 $iPrint version:$tPredicting structured data.$dCambridge, Mass. : MIT Press, ©2007$z9780262026178$z0262026171$w(DLC) 2006047001$w(OCoLC)74965922
830 0 $aNeural information processing series.
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio9254242$zAll EBSCO eBooks
852 8 $blweb$hEBOOKS