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Structured prediction by joint kernel support estimation

Abstract:

Discriminative techniques, such as conditional random fields (CRFs) or structure aware maximum-margin techniques (maximum margin Markov networks (M³N), structured output support vector machines (S-SVM)), are state-of-the-art in the prediction of structured data. However, to achieve good results these techniques require complete and reliable ground truth, which is not always available in realistic problems. Furthermore, training either CRFs or margin-based techniques is computationally costly,...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/s10994-009-5111-0

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Institution:
Max Planck Institute for Biological Cybernetics, Tübingen, Germany
Role:
Author
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Institution:
"Max Planck Institute for Biological Cybernetics, Tübingen, Germany", "University of Oxford"
Department:
Mathematical,Physical & Life Sciences Division - Engineering Science
Role:
Author
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Name:
PASCAL2 network of excellence
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Name:
EC project CLASS, IST 027978
Publisher:
Springer
Journal:
Machine Learning More from this journal
Volume:
77
Issue:
2-3
Pages:
249-269
Publication date:
2009-12-01
DOI:
EISSN:
1573-0565
ISSN:
0885-6125
Language:
English
Keywords:
Subjects:
UUID:
uuid:c806c9d4-21f3-41f2-850b-0389f32c3f7f
Local pid:
ora:3619
Deposit date:
2010-04-08

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