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Volumn , Issue , 2009, Pages 1657-1664

Hierarchical semi-Markov conditional random fields for recursive sequential data

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE SEGMENTATION; INFERENCE ENGINES; LEARNING ALGORITHMS; MARKOV PROCESSES; POLYNOMIAL APPROXIMATION; SECURITY SYSTEMS;

EID: 79952553416     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (20)

References (12)
  • 1
    • 9444228194 scopus 로고    scopus 로고
    • Hierarchical hidden Markov models with general state hierarchy
    • San Jose, CA, Jul
    • H. H. Bui, D. Q. Phung, and S. Venkatesh. Hierarchical hidden Markov models with general state hierarchy. In AAAI, pages 324-329, San Jose, CA, Jul 2004.
    • (2004) AAAI , pp. 324-329
    • Bui, H.H.1    Phung, D.Q.2    Venkatesh, S.3
  • 2
    • 0032119668 scopus 로고    scopus 로고
    • The hierarchical hidden Markov model: Analysis and applications
    • S. Fine, Y. Singer, and N. Tishby. The hierarchical hidden Markov model: Analysis and applications. Machine Learning, 32(1):41-62, 1998.
    • (1998) Machine Learning , vol.32 , Issue.1 , pp. 41-62
    • Fine, S.1    Singer, Y.2    Tishby, N.3
  • 3
    • 9444286980 scopus 로고    scopus 로고
    • Interactive information extraction with constrained conditional random fields
    • San Jose, CA
    • T. Kristjannson, A. Culotta, P. Viola, and A. McCallum. Interactive information extraction with constrained conditional random fields. In AAAI, pages 412-418, San Jose, CA, 2004.
    • (2004) AAAI , pp. 412-418
    • Kristjannson, T.1    Culotta, A.2    Viola, P.3    McCallum, A.4
  • 4
    • 0142192295 scopus 로고    scopus 로고
    • Conditional random fields: Probabilistic models for segmenting and labeling sequence data
    • J. Lafferty, A.McCallum, and F. Pereira. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In ICML, pages 282-289, 2001.
    • (2001) ICML , pp. 282-289
    • Lafferty, J.1    McCallum, A.2    Pereira, F.3
  • 7
    • 24644492941 scopus 로고    scopus 로고
    • Learning and detecting activities from movement trajectories using the hierarchical hidden Markov models
    • Jun
    • N. Nguyen, D. Phung, S. Venkatesh, and H. H. Bui. Learning and detecting activities from movement trajectories using the hierarchical hidden Markov models. In CVPR, volume 2, pages 955-960, Jun 2005.
    • (2005) CVPR , vol.2 , pp. 955-960
    • Nguyen, N.1    Phung, D.2    Venkatesh, S.3    Bui, H.H.4
  • 8
    • 34047192804 scopus 로고    scopus 로고
    • Semi-Markov conditional random fields for information extraction
    • S. Sarawagi and W. W. Cohen. Semi-Markov conditional random fields for information extraction. In NIPS. 2004.
    • (2004) NIPS
    • Sarawagi, S.1    Cohen, W.W.2
  • 10
    • 33947615175 scopus 로고    scopus 로고
    • Dynamic conditional random fields: Factorized probabilistic models for labeling and segmenting sequence data
    • C. Sutton, A. McCallum, and K. Rohanimanesh. Dynamic conditional random fields: Factorized probabilistic models for labeling and segmenting sequence data. JMLR, 8:693-723, Mar 2007. (Pubitemid 46491655)
    • (2007) Journal of Machine Learning Research , vol.8 , pp. 693-723
    • Sutton, C.1    McCallum, A.2    Rohanimanesh, K.3
  • 12
    • 58349114205 scopus 로고    scopus 로고
    • Scene segmentation with CRFs learned from partially labeled images
    • MIT Press
    • J. Verbeek and B. Triggs. Scene segmentation with CRFs learned from partially labeled images. In Advances in Neural Information Processing Systems 20, pages 1553-1560. MIT Press, 2008.
    • (2008) Advances in Neural Information Processing Systems , vol.20 , pp. 1553-1560
    • Verbeek, J.1    Triggs, B.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.