Conditional random field

Results: 247



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61arXiv:1301.4168v2 [cs.LG] 16 MarHerded Gibbs Sampling Luke Bornn Harvard University

arXiv:1301.4168v2 [cs.LG] 16 MarHerded Gibbs Sampling Luke Bornn Harvard University

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Source URL: www.ics.uci.edu

Language: English - Date: 2013-04-19 06:38:10
62Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study Sanjiv Kumar, Jonas August, and Martial Hebert The Robotics Institute, Carnegie Mellon University Pittsburgh, PA 15213

Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study Sanjiv Kumar, Jonas August, and Martial Hebert The Robotics Institute, Carnegie Mellon University Pittsburgh, PA 15213

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Source URL: www.sanjivk.com

Language: English - Date: 2010-06-01 18:50:53
63Hidden-Unit Conditional Random Fields  Laurens van der Maaten Max Welling

Hidden-Unit Conditional Random Fields Laurens van der Maaten Max Welling

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Source URL: lvdmaaten.github.io

Language: English - Date: 2015-06-09 09:51:41
64Using active learning and pre-tagging for annotating clinical findings in health record text Maria Skeppstedt, Hercules Dalianis Dept. of Computer and Systems Sciences (DSV) Stockholm University, Forum 100, Kista,

Using active learning and pre-tagging for annotating clinical findings in health record text Maria Skeppstedt, Hercules Dalianis Dept. of Computer and Systems Sciences (DSV) Stockholm University, Forum 100, Kista,

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Source URL: www.zora.uzh.ch

Language: English - Date: 2012-09-21 10:15:44
65R Foundations and Trends in Machine Learning Vol. 4, No–373 c 2012 C. Sutton and A. McCallum

R Foundations and Trends in Machine Learning Vol. 4, No–373 c 2012 C. Sutton and A. McCallum

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Source URL: homepages.inf.ed.ac.uk

Language: English - Date: 2012-08-27 13:34:18
66Semi-Supervised Sequence Labeling with Self-Learned Features Yanjun Qi∗ , Pavel Kuksa† , Ronan Collobert∗ , Kunihiko Sadamasa∗ , Koray Kavukcuoglu‡ and Jason Weston§ ∗ Machine Learning Department, NEC Labs A

Semi-Supervised Sequence Labeling with Self-Learned Features Yanjun Qi∗ , Pavel Kuksa† , Ronan Collobert∗ , Kunihiko Sadamasa∗ , Koray Kavukcuoglu‡ and Jason Weston§ ∗ Machine Learning Department, NEC Labs A

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Source URL: ronan.collobert.com

Language: English - Date: 2009-09-30 13:22:00
67Named Entity Generation using Sampling-based Structured Prediction Guillaume Bouchard Xerox Research Centre Europe 6 Chemin de MaupertuisMeylan, France

Named Entity Generation using Sampling-based Structured Prediction Guillaume Bouchard Xerox Research Centre Europe 6 Chemin de MaupertuisMeylan, France

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Source URL: www.aclweb.org

Language: English - Date: 2010-10-07 05:30:10
68Concise Integer Linear Programming Formulations for Dependency Parsing ∗ Andr´e F. T. Martins∗† Noah A. Smith∗ Eric P. Xing∗ School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA

Concise Integer Linear Programming Formulations for Dependency Parsing ∗ Andr´e F. T. Martins∗† Noah A. Smith∗ Eric P. Xing∗ School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA

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Source URL: www.cs.cmu.edu

Language: English - Date: 2009-05-19 09:57:02
691370  IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 36,

1370 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 36,

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Source URL: cvgl.stanford.edu

Language: English - Date: 2014-10-15 19:57:00
70

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Source URL: www.comp.nus.edu.sg

Language: English - Date: 2006-03-20 19:18:22