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Volumn , Issue , 2003, Pages 145-152

Investigating Loss Functions and Optimization Methods for Discriminative Learning of Label Sequences

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS;

EID: 85113387701     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/1119355.1119374     Document Type: Conference Paper
Times cited : (31)

References (14)
  • 3
    • 0040044720 scopus 로고    scopus 로고
    • Discriminative reranking for natural language parsing
    • M. Collins. 2000. Discriminative reranking for natural language parsing. In Proceedings of ICML 2002.
    • (2000) Proceedings of ICML 2002
    • Collins, M.1
  • 4
    • 85045072379 scopus 로고    scopus 로고
    • Ranking algorithms for named-entity extraction: Boosting and the voted perceptron
    • M. Collins. 2002. Ranking algorithms for named-entity extraction: Boosting and the voted perceptron. In Proceedings of ACL’02.
    • (2002) Proceedings of ACL’02
    • Collins, M.1
  • 8
    • 0142192295 scopus 로고    scopus 로고
    • Conditional random fields: Probabilistic models for segmenting and labeling sequence data
    • J. Lafferty, A. McCallum, and F. Pereira. 2001. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proceedings of ICML2001.
    • (2001) Proceedings of ICML2001
    • Lafferty, J.1    McCallum, A.2    Pereira, F.3
  • 9
    • 0000747663 scopus 로고    scopus 로고
    • Maximum Entropy Markov Models for Information Extraction and Segmentation
    • A. McCallum, D. Freitag, and F. Pereira. 2000. Maximum Entropy Markov Models for Information Extraction and Segmentation. In Proceedings of ICML 2000.
    • (2000) Proceedings of ICML 2000
    • McCallum, A.1    Freitag, D.2    Pereira, F.3
  • 12
    • 0032660854 scopus 로고    scopus 로고
    • Learning to parse natural language with maximum entropy models
    • Adwait Ratnaparkhi. 1999. Learning to parse natural language with maximum entropy models. Machine Learning, 34(1-3):151–175.
    • (1999) Machine Learning , vol.34 , Issue.1-3 , pp. 151-175
    • Ratnaparkhi, Adwait1
  • 13
    • 0033281701 scopus 로고    scopus 로고
    • Improved boosting algorithms using confidence-rated predictions
    • R. Schapire and Y. Singer. 1999. Improved boosting algorithms using confidence-rated predictions. Machine Learning, 37(3):297–336.
    • (1999) Machine Learning , vol.37 , Issue.3 , pp. 297-336
    • Schapire, R.1    Singer, Y.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.