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Volumn , Issue , 2004, Pages 1127-1131

A semi-supervised classification method based on transduction of labeled data

Author keywords

[No Author keywords available]

Indexed keywords

DATA REDUCTION; ERROR ANALYSIS; KNOWLEDGE ACQUISITION; LEARNING SYSTEMS; PATTERN RECOGNITION; PROBLEM SOLVING;

EID: 11244337633     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (2)

References (9)
  • 2
    • 11244279472 scopus 로고    scopus 로고
    • Learning from partially labeled data
    • Department of Electrical Engineering and Computer Science, Massachusetts Institue of Technology
    • M.O. Szummer, "Learning from partially labeled data," Doctorial Dissertation, Department of Electrical Engineering and Computer Science, Massachusetts Institue of Technology, 2002.
    • (2002) Doctorial Dissertation
    • Szummer, M.O.1
  • 3
    • 0005977840 scopus 로고    scopus 로고
    • Learning with labeled and unlabeled data
    • University of Edinburgh
    • M. Seeger, "Learning with labeled and unlabeled data," Technical Report, University of Edinburgh, 2001.
    • (2001) Technical Report
    • Seeger, M.1
  • 4
    • 0029195475 scopus 로고
    • On the exponential value of labeled samples
    • Jan.
    • V. Castelli, and T.M. Cover, "On the exponential value of labeled samples," Pattern Recognition Letters, 16, pp.105-111, Jan. 1995.
    • (1995) Pattern Recognition Letters , vol.16 , pp. 105-111
    • Castelli, V.1    Cover, T.M.2
  • 6
    • 0016421071 scopus 로고
    • The estimation of the gradient of a density function, with application in pattern recognition
    • Jan.
    • K. Fukunaga, and L.D. Hosteller, "The estimation of the gradient of a density function, with application in pattern recognition," IEEE Transactions on Information Theory, Vol. IT-21, No. 1, Jan. 1975.
    • (1975) IEEE Transactions on Information Theory , vol.IT-21 , Issue.1
    • Fukunaga, K.1    Hosteller, L.D.2
  • 9
    • 0003857778 scopus 로고    scopus 로고
    • A gentle tutorial of the EM algorithm and its application to parameter estimation of Gaussian mixture and hidden Markov models
    • TR-97-021
    • J.A. Bilmes, "A gentle tutorial of the EM algorithm and its application to parameter estimation of Gaussian mixture and hidden Markov models," ICSI Technical Report, TR-97-021, 1997.
    • (1997) ICSI Technical Report
    • Bilmes, J.A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.