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Volumn , Issue , 2013, Pages 32-41

Hinge-loss Markov random fields: Convex inference for structured prediction

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATE INFERENCE; CONTINUOUS VARIABLES; INFERENCE ALGORITHM; LOG-CONCAVE DENSITY FUNCTION; MARKOV RANDOM FIELDS; PREDICTIVE PERFORMANCE; STATE-OF-THE-ART METHODS; STRUCTURED PREDICTION;

EID: 84888154242     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (64)

References (26)
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    • M. Collins. Discriminative training methods for hidden Markov models: theory and experiments with perceptron algorithms. In Empirical Methods in Natural Language Processing, 2002.
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    • Collins, M.1
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    • Eigentaste: A constant time collaborative filtering algorithm
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    • K. Goldberg, T. Roeder, D. Gupta, and C. Perkins. Eigentaste: A constant time collaborative filtering algorithm. Information Retrieval, 4(2): 133-151, July 2001.
    • (2001) Information Retrieval , vol.4 , Issue.2 , pp. 133-151
    • Goldberg, K.1    Roeder, T.2    Gupta, D.3    Perkins, C.4
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    • Cutting-plane training of structural SVMs
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    • Markov logic networks
    • M. Richardson and P. Domingos. Markov logic networks. Machine Learning, 62(1-2): 107-136, 2006.
    • (2006) Machine Learning , vol.62 , Issue.1-2 , pp. 107-136
    • Richardson, M.1    Domingos, P.2
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    • Graphical models, exponential families, and variational inference
    • January
    • M. Wainwright and M. Jordan. Graphical models, exponential families, and variational inference. Foundations and Trends in Machine Learning, 1(1-2), January 2008.
    • (2008) Foundations and Trends in Machine Learning , vol.1 , Issue.1-2
    • Wainwright, M.1    Jordan, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.