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Predicting structured data

Author: Gökhan BakIr; Neural Information Processing Systems Foundation.; et al
Publisher: Cambridge, Mass. : MIT Press, ©2007.
Series: Neural information processing series.
Edition/Format:   Book : EnglishView all editions and formats
Database:WorldCat
Summary:

State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.

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Additional Physical Format: Online version:
Predicting structured data.
Cambridge, Mass. : MIT Press, c2007
(OCoLC)608103137
Document Type: Book
All Authors / Contributors: Gökhan BakIr; Neural Information Processing Systems Foundation.; et al
ISBN: 9780262026178 0262026171
OCLC Number: 74965922
Notes: Collected papers based on talks presented at two Neural Information Processing Systems workshops.
Description: viii, 348 p. : ill. ; 26 cm.
Contents: Measuring Similarity with Kernels --
Discriminative Models --
Modeling Structure via Graphical Models --
Joint Kernel Maps / Jason Weston ... [et al.] --
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 ... [et al.] --
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 ... [et al.] --
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.
Series Title: Neural information processing series.
Responsibility: edited by Gökhan Bakır ... [et al.].

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