|
|
|
|
| LEADER |
02991nam a2200433 a 4500 |
| 001 |
1908439 |
| 005 |
20171111234746.0 |
| 008 |
070925s2007 maua ob 001 0 eng d |
| 020 |
|
|
|a 9780262255691
|q (electronic bk.)
|
| 020 |
|
|
|a 0262255693
|q (electronic bk.)
|
| 020 |
|
|
|a 9781429499170
|q (electronic bk.)
|
| 020 |
|
|
|a 1429499176
|q (electronic bk.)
|z 9780262026178
|q (alk. paper)
|q (alk. paper)
|
| 040 |
|
|
|a N$T
|b eng
|e pn
|z 0262026171
|
| 050 |
|
4 |
|a Q325.5
|b .P74 2007eb
|
| 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.
|
| 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.
|
| 650 |
|
0 |
|a Machine learning.
|
| 650 |
|
0 |
|a Computer algorithms.
|
| 650 |
|
0 |
|a Kernel functions.
|
| 650 |
|
0 |
|a Data structures (Computer science)
|
| 650 |
|
7 |
|a COMPUTERS
|x Enterprise Applications
|x Business Intelligence Tools.
|
| 650 |
|
7 |
|a COMPUTERS
|x Intelligence (AI) & Semantics.
|
| 650 |
|
7 |
|a Computer algorithms.
|
| 650 |
|
7 |
|a Data structures (Computer science)
|
| 650 |
|
7 |
|a Kernel functions.
|
| 650 |
|
7 |
|a Machine learning.
|
| 650 |
|
7 |
|a Lernen
|x (Informatik)
|x Kernel (Informatik)
|
| 650 |
|
7 |
|a Lernen
|x (Informatik)
|x Strukturlogik.
|
| 650 |
|
7 |
|a Strukturlogik
|x Lernen (Informatik)
|
| 650 |
|
7 |
|a Kernel
|x (Informatik)
|
| 700 |
1 |
|
|a BakIr, Gökhan.
|x Lernen (Informatik)
|
| 710 |
2 |
|
|a Neural Information Processing Systems Foundation.
|
| 856 |
4 |
0 |
|u http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=202394
|
| 952 |
|
|
|a CY-NiOUC
|b 5a0467056c5ad14ac1eeffe4
|c 998a
|d 945l
|e -
|t 1
|x m
|z Books
|
