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Volumn 1, Issue , 2011, Pages 852-857

Co-training as a human collaboration policy

Author keywords

[No Author keywords available]

Indexed keywords

BASE LEARNERS; CO-TRAINING; CO-TRAINING ALGORITHM; COLLABORATION POLICIES; EMPIRICAL STUDIES; LABELINGS; MACHINE-LEARNING; TRAINING SETS;

EID: 80055035640     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (5)

References (13)
  • 2
    • 77950343112 scopus 로고    scopus 로고
    • A discriminative model for semi-supervised learning
    • Balcan, M.-F., and Blum, A. 2010. A discriminative model for semi-supervised learning. Journal of the ACM 57(3).
    • (2010) Journal of the ACM , vol.57 , Issue.3
    • Balcan, M.-F.1    Blum, A.2
  • 3
    • 0031620208 scopus 로고    scopus 로고
    • Combining labeled and unlabeled data with co-training
    • Blum, A., and Mitchell, T. 1998. Combining labeled and unlabeled data with co-training. In COLT.
    • (1998) COLT
    • Blum, A.1    Mitchell, T.2
  • 5
    • 80055029811 scopus 로고    scopus 로고
    • Two-view feature generation model for semi-supervised learning
    • Johnson, R., and Zhang, T. 2007. Two-view feature generation model for semi-supervised learning. In ICML.
    • (2007) ICML
    • Johnson, R.1    Zhang, T.2
  • 7
    • 0038646126 scopus 로고    scopus 로고
    • Comparing supervised and unsupervised category learning
    • Love, B. C. 2002. Comparing supervised and unsupervised category learning. Psychonomic Bulletin and Review 9:829-835.
    • (2002) Psychonomic Bulletin and Review , vol.9 , pp. 829-835
    • Love, B.C.1
  • 8
    • 85136905861 scopus 로고    scopus 로고
    • Analyzing the effectiveness and applicability of co-training
    • Nigam, K., and Ghani, R. 2000. Analyzing the effectiveness and applicability of co-training. In CIKM.
    • (2000) CIKM
    • Nigam, K.1    Ghani, R.2
  • 9
    • 0002573701 scopus 로고    scopus 로고
    • Learning to classify integral-dimension stimuli
    • Nosofsky, R. M., and Palmeri, T. J. 1996. Learning to classify integral-dimension stimuli. Psychonomic Bulletin and Review 3(2):222-226. (Pubitemid 126421516)
    • (1996) Psychonomic Bulletin and Review , vol.3 , Issue.2 , pp. 222-226
    • Nosofsky, R.M.1    Palmeri, T.J.2
  • 10
    • 0022686961 scopus 로고
    • Attention, similarity, and the identification-categorization relationship
    • Nosofsky, R. M. 1986. Attention, similarity, and the identification- categorization relationship. Journal of Experimental Psychology: General 115(1):39-57.
    • (1986) Journal of Experimental Psychology: General , vol.115 , Issue.1 , pp. 39-57
    • Nosofsky, R.M.1
  • 11
    • 0002994064 scopus 로고
    • Attention and the metric structure of the stimulus space
    • Shepard, R. N. 1964. Attention and the metric structure of the stimulus space. Journal of Mathematical Psychology 1:54-87.
    • (1964) Journal of Mathematical Psychology , vol.1 , pp. 54-87
    • Shepard, R.N.1
  • 12
    • 64749109194 scopus 로고    scopus 로고
    • Semisupervised category learning: The impact of feedback in learning the information-integration task
    • Vandist, K.; Schryver, M. D.; and Rosseel, Y. 2009. Semisupervised category learning: The impact of feedback in learning the information- integration task. Attention, Perception, & Psychophysics 71(2):328-341.
    • (2009) Attention, Perception, & Psychophysics , vol.71 , Issue.2 , pp. 328-341
    • Vandist, K.1    Schryver, M.D.2    Rosseel, Y.3
  • 13
    • 28244448186 scopus 로고    scopus 로고
    • Tri-training: Exploiting unlabeled data using three classifiers
    • DOI 10.1109/TKDE.2005.186
    • Zhou, Z.-H., and Li, M. 2005. Tri-training: exploiting unlabeled data using three classifiers. IEEE Transactions on Knowledge and Data Engineering 17(11):1529-1541. (Pubitemid 41704840)
    • (2005) IEEE Transactions on Knowledge and Data Engineering , vol.17 , Issue.11 , pp. 1529-1541
    • Zhou, Z.-H.1    Li, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.