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  Density Estimation of Structured Outputs in Reproducing Kernel Hilbert Spaces

Altun, Y., & Smola, A. (2007). Density Estimation of Structured Outputs in Reproducing Kernel Hilbert Spaces. In G. Bakır, T. Hofmann, B. Schölkopf, A. Smola, B. Taskar, & S. Vishwanathan (Eds.), Predicting Structured Data (pp. 283-300). Cambridge, MA, USA: MIT Press.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-CC03-E Version Permalink: http://hdl.handle.net/21.11116/0000-0003-ECE6-0
Genre: Book Chapter

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 Creators:
Altun, Y1, Author              
Smola, A, Author              
Affiliations:
1External Organizations, ou_persistent22              

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 Abstract: In this paper we study the problem of estimating conditional probability distributions for structured output prediction tasks in Reproducing Kernel Hilbert Spaces. More specically, we prove decomposition results for undirected graphical models, give constructions for kernels, and show connections to Gaussian Process classi- cation. Finally we present ecient means of solving the optimization problem and apply this to label sequence learning. Experiments on named entity recognition and pitch accent prediction tasks demonstrate the competitiveness of our approach.

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 Dates: 2007-09
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 5702
 Degree: -

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Title: Predicting Structured Data
Source Genre: Book
 Creator(s):
Bakır, GH1, Editor            
Hofmann, T, Editor            
Schölkopf, B1, Editor            
Smola, AJ, Editor            
Taskar, B, Editor
Vishwanathan, SVN, Editor
Affiliations:
1 Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795            
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: 348 Volume / Issue: - Sequence Number: - Start / End Page: 283 - 300 Identifier: ISBN: 978-0-262-02617-8