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Volumn , Issue , 2008, Pages 93-

Semi-supervised learning by disagreement

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EID: 57949117175     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/GRC.2008.4664785     Document Type: Conference Paper
Times cited : (16)

References (14)
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    • Improve computer-aided diagnosis with machine learning techniques using undiagnosed samples
    • M. Li, Z.-H. Zhou. Improve computer-aided diagnosis with machine learning techniques using undiagnosed samples. IEEE TSMC-A, vol.37, no.6, 2007.
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    • Li, M.1    Zhou, Z.-H.2
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    • Analyzing co-training style algorithms
    • W. Wang, Z.-H. Zhou. Analyzing co-training style algorithms. ECML, 2007.
    • (2007) ECML
    • Wang, W.1    Zhou, Z.-H.2
  • 7
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    • On multi-view active learning and the combination with semi-supervised learning
    • W.Wang, Z.-H. Zhou. On multi-view active learning and the combination with semi-supervised learning. ICML, 2008.
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    • Wang, W.1    Zhou, Z.-H.2
  • 8
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    • Enhancing relevance feedback in image retrieval using unlabeled data
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    • Zhou, Z.-H.1    Chen, K.-J.2    Dai, H.-B.3
  • 9
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    • Exploiting unlabeled data in content-based image retrieval
    • Z.-H. Zhou, K.-J. Chen, Y. Jiang. Exploiting unlabeled data in content-based image retrieval. ECML, 2004.
    • (2004) ECML
    • Zhou, Z.-H.1    Chen, K.-J.2    Jiang, Y.3
  • 10
    • 84880742718 scopus 로고    scopus 로고
    • Semi-supervised regression with cotraining
    • Z.-H. Zhou, M. Li. Semi-supervised regression with cotraining. IJCAI, 2005.
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    • Zhou, Z.-H.1    Li, M.2
  • 11
    • 28244448186 scopus 로고    scopus 로고
    • Tri-training: Exploiting unlabeled data using three classifiers
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  • 12
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    • Semi-supervised regression with cotraining style algorithms
    • Z.-H. Zhou, M. Li. Semi-supervised regression with cotraining style algorithms. IEEE TKDE, vol.19, no.11, 2007.
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    • Zhou, Z.-H.1    Li, M.2
  • 13
    • 57949083825 scopus 로고    scopus 로고
    • Semi-supervised learning with very few labeled training examples
    • Z.-H. Zhou, D.-C. Zhan, Q. Yang. Semi-supervised learning with very few labeled training examples. AAAI, 2007.
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    • Zhou, Z.-H.1    Zhan, D.-C.2    Yang, Q.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.