Cargando…

Predicting structured data /

State-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 sat...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: Neural Information Processing Systems Foundation
Otros Autores: BakIr, Gökhan
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cambridge, Mass. : MIT Press, ©2007.
Colección:Neural information processing series.
Temas:
Acceso en línea:Texto completo

MARC

LEADER 00000cam a2200000 a 4500
001 EBSCO_ocn173281492
003 OCoLC
005 20231017213018.0
006 m o d
007 cr cnu---unuuu
008 070925s2007 maua ob 001 0 eng d
040 |a N$T  |b eng  |e pn  |c N$T  |d YDXCP  |d OCLCQ  |d N$T  |d IDEBK  |d OCLCQ  |d SGE  |d ZCU  |d OCLCQ  |d IEEEE  |d OCLCE  |d OCLCQ  |d OCLCF  |d P4I  |d NLGGC  |d OCLCQ  |d PIFSG  |d OCLCQ  |d NJR  |d WY@  |d OCLCQ  |d VTS  |d MERER  |d OCLCQ  |d AU@  |d MITPR  |d LEAUB  |d OCLCQ  |d OCLCO  |d HS0  |d RDF  |d LUN  |d SFB  |d VT2  |d DST  |d VHC  |d OCLCQ  |d OCLCO  |d ANO  |d OCL  |d OCLCQ  |d OCLCO 
015 |a GBA742903  |2 bnb 
016 7 |a 013761175  |2 Uk 
019 |a 297265452  |a 608103137  |a 991958620  |a 1011895731  |a 1058072733  |a 1109190711  |a 1170016188  |a 1170924193  |a 1280245345  |a 1281467962  |a 1286901435  |a 1300587678  |a 1303355564  |a 1303412063 
020 |a 9780262255691  |q (electronic bk.) 
020 |a 0262255693  |q (electronic bk.) 
020 |a 9781429499170  |q (electronic bk.) 
020 |a 1429499176  |q (electronic bk.) 
020 |a 9786612096075 
020 |a 6612096071 
020 |a 1282096079 
020 |a 9781282096073 
020 |a 9780262528047  |q (print) 
020 |a 0262528045 
020 |z 9780262026178  |q (alk. paper) 
020 |z 0262026171  |q (alk. paper) 
024 8 |a 2550618 
029 1 |a AU@  |b 000051284538 
029 1 |a AU@  |b 000051404150 
029 1 |a AU@  |b 000067494259 
029 1 |a DEBBG  |b BV042957125 
029 1 |a DEBSZ  |b 42218697X 
035 |a (OCoLC)173281492  |z (OCoLC)297265452  |z (OCoLC)608103137  |z (OCoLC)991958620  |z (OCoLC)1011895731  |z (OCoLC)1058072733  |z (OCoLC)1109190711  |z (OCoLC)1170016188  |z (OCoLC)1170924193  |z (OCoLC)1280245345  |z (OCoLC)1281467962  |z (OCoLC)1286901435  |z (OCoLC)1300587678  |z (OCoLC)1303355564  |z (OCoLC)1303412063 
037 |a 7443  |b MIT Press 
037 |a 9780262255691  |b MIT Press 
042 |a dlr 
050 4 |a Q325.5  |b .P74 2007eb 
072 7 |a COM  |x 005030  |2 bisacsh 
072 7 |a COM  |x 004000  |2 bisacsh 
082 0 4 |a 006.3/1  |2 22 
049 |a UAMI 
245 0 0 |a Predicting structured data /  |c edited by Gökhan Bakır [and others]. 
260 |a Cambridge, Mass. :  |b MIT Press,  |c ©2007. 
300 |a 1 online resource (viii, 348 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Advances in neural information processing systems 
500 |a Collected papers based on talks presented at two Neural Information Processing Systems workshops. 
504 |a Includes bibliographical references (pages 319-340) and index. 
505 0 |a Measuring 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 |3 Use copy  |f Restrictions unspecified  |2 star  |5 MiAaHDL 
533 |a Electronic reproduction.  |b [Place of publication not identified] :  |c HathiTrust Digital Library,  |d 2010.  |5 MiAaHDL 
538 |a Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.  |u http://purl.oclc.org/DLF/benchrepro0212  |5 MiAaHDL 
583 1 |a digitized  |c 2010  |h HathiTrust Digital Library  |l committed to preserve  |2 pda  |5 MiAaHDL 
588 0 |a Print version record. 
546 |a English. 
520 |a State-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 
590 |a eBooks on EBSCOhost  |b EBSCO eBook Subscription Academic Collection - Worldwide 
650 0 |a Machine learning. 
650 0 |a Computer algorithms. 
650 0 |a Kernel functions. 
650 0 |a Data structures (Computer science) 
650 0 |a Algorithms. 
650 2 |a Algorithms 
650 2 |a Machine Learning 
650 6 |a Apprentissage automatique. 
650 6 |a Algorithmes. 
650 6 |a Noyaux (Mathématiques) 
650 6 |a Structures de données (Informatique) 
650 7 |a algorithms.  |2 aat 
650 7 |a COMPUTERS  |x Enterprise Applications  |x Business Intelligence Tools.  |2 bisacsh 
650 7 |a COMPUTERS  |x Intelligence (AI) & Semantics.  |2 bisacsh 
650 7 |a Algorithms  |2 fast 
650 7 |a Computer algorithms  |2 fast 
650 7 |a Data structures (Computer science)  |2 fast 
650 7 |a Kernel functions  |2 fast 
650 7 |a Machine learning  |2 fast 
650 7 |a Lernen  |x (Informatik)  |x Kernel (Informatik)  |2 idsbb 
650 7 |a Lernen  |x (Informatik)  |x Strukturlogik.  |2 idsbb 
650 7 |a Strukturlogik  |x Lernen (Informatik)  |2 idsbb 
650 7 |a Kernel  |x (Informatik)  |x Lernen (Informatik)  |2 idsbb 
653 |a COMPUTER SCIENCE/Machine Learning & Neural Networks 
700 1 |a BakIr, Gökhan. 
710 2 |a Neural Information Processing Systems Foundation. 
776 0 8 |i Print version:  |t Predicting structured data.  |d Cambridge, Mass. : MIT Press, ©2007  |z 9780262026178  |z 0262026171  |w (DLC) 2006047001  |w (OCoLC)74965922 
830 0 |a Neural information processing series. 
856 4 0 |u https://ebsco.uam.elogim.com/login.aspx?direct=true&scope=site&db=nlebk&AN=202394  |z Texto completo 
938 |a EBSCOhost  |b EBSC  |n 202394 
938 |a IEEE  |b IEEE  |n 6267216 
938 |a YBP Library Services  |b YANK  |n 2709816 
938 |a YBP Library Services  |b YANK  |n 3410815 
994 |a 92  |b IZTAP