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  Exponential Families for Conditional Random Fields

Altun, Y., Smola, A., & Hofmann, T. (2004). Exponential Families for Conditional Random Fields. In C. Meek, M. Chickering, & J. Halpern (Eds.), UAI '04: 20th Annual Conference on Uncertainty in Artificial Intelligence (pp. 2-9). New York, NY, USA: ACM Press.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-D8A3-3 Version Permalink: https://hdl.handle.net/21.11116/0000-0005-52E3-E
Genre: Conference Paper

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https://dl.acm.org/citation.cfm?id=1036844 (Publisher version)
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 Creators:
Altun, Y, Author           
Smola, AJ, Author           
Hofmann, T1, 2, Author           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: In this paper we define conditional random fields in reproducing kernel Hilbert spaces and show connections to Gaussian Process classification. More specifically, we prove decomposition results for undirected graphical models and we give constructions for kernels. Finally we present efficient means of solving the optimization problem using reduced rank decompositions and we show how stationarity can be exploited efficiently in the optimization process.

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 Dates: 2004-07
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: BibTex Citekey: 2741
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Title: 20th Annual Conference on Uncertainty in Artificial Intelligence (UAI 2004)
Place of Event: Banff, Canada
Start-/End Date: 2004-07-07 - 2004-07-11

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Title: UAI '04: 20th Annual Conference on Uncertainty in Artificial Intelligence
Source Genre: Proceedings
 Creator(s):
Meek, C, Editor
Chickering, M, Editor
Halpern, J, Editor
Affiliations:
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Publ. Info: New York, NY, USA : ACM Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 2 - 9 Identifier: ISBN: 0-9749039-0-6