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Volumn , Issue , 2010, Pages 299-306

SED: Supervised experimental design and its application to text classification

Author keywords

Active learning; Convex optimization; Supervised experimental design; Text classification

Indexed keywords

ACTIVE LEARNING; ACTIVE LEARNING METHODS; EXPERIMENTAL DESIGN; LABEL INFORMATION; LABELED DATA; STATE-OF-THE-ART PERFORMANCE; TEXT CLASSIFICATION; UNLABELED DATA;

EID: 77956033149     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1835449.1835501     Document Type: Conference Paper
Times cited : (9)

References (25)
  • 1
    • 0000710299 scopus 로고
    • Queries and concept learning
    • D. Angluin. Queries and concept learning. Mach. Learn., 2(4):319-342, 1988.
    • (1988) Mach. Learn. , vol.2 , Issue.4 , pp. 319-342
    • Angluin, D.1
  • 3
    • 0028424239 scopus 로고
    • Improving generalization with active learning
    • D. Cohn, L. Atlas, and R. Ladner. Improving generalization with active learning. Mach. Learn., 15(2):201-221, 1994.
    • (1994) Mach. Learn. , vol.15 , Issue.2 , pp. 201-221
    • Cohn, D.1    Atlas, L.2    Ladner, R.3
  • 5
    • 4644367942 scopus 로고    scopus 로고
    • An efficient boosting algorithm for combining preferences
    • Y. Freund, R. Iyer, R. E. Schapire, and Y. Singer. An efficient boosting algorithm for combining preferences. J. Mach. Learn. Res., 4:933-969, 2003.
    • (2003) J. Mach. Learn. Res. , vol.4 , pp. 933-969
    • Freund, Y.1    Iyer, R.2    Schapire, R.E.3    Singer, Y.4
  • 6
    • 84880855398 scopus 로고    scopus 로고
    • Optimistic active learning using mutual information
    • Y. Guo and R. Greiner. Optimistic active learning using mutual information. In IJCAI, 2007.
    • (2007) IJCAI
    • Guo, Y.1    Greiner, R.2
  • 7
    • 79551702937 scopus 로고    scopus 로고
    • Discriminative batch mode active learning
    • Y. Guo and D. Schuurmans. Discriminative batch mode active learning. In NIPS, 2007.
    • (2007) NIPS
    • Guo, Y.1    Schuurmans, D.2
  • 8
    • 36448966739 scopus 로고    scopus 로고
    • Laplacian optimal design for image retrieval
    • X. He, W. Min, D. Cai, and K. Zhou. Laplacian optimal design for image retrieval. In SIGIR, 2007.
    • (2007) SIGIR
    • He, X.1    Min, W.2    Cai, D.3    Zhou, K.4
  • 9
    • 34250637963 scopus 로고    scopus 로고
    • Large-scale text categorization by batch mode active learning
    • S. C. Hoi, R. Jin, and M. R. Lyu. Large-scale text categorization by batch mode active learning. In WWW, 2006.
    • (2006) WWW
    • Hoi, S.C.1    Jin, R.2    Lyu, M.R.3
  • 10
    • 33749263388 scopus 로고    scopus 로고
    • Batch mode active learning and its application to medical image classification
    • S. C. Hoi, R. Jin, J. Zhu, and M. R. Lyu. Batch mode active learning and its application to medical image classification. In ICML, 2006.
    • (2006) ICML
    • Hoi, S.C.1    Jin, R.2    Zhu, J.3    Lyu, M.R.4
  • 11
    • 85013879626 scopus 로고
    • A sequential algorithm for training text classifiers
    • D. D. Lewis and W. A. Gale. A sequential algorithm for training text classifiers. In SIGIR, 1994.
    • (1994) SIGIR
    • Lewis, D.D.1    Gale, W.A.2
  • 12
    • 84876811202 scopus 로고    scopus 로고
    • RCV1: A new benchmark collection for text categorization research
    • D. D. Lewis, Y. Yang, T. G. Rose, and F. Li. RCV1: A new benchmark collection for text categorization research. J. Mach. Learn. Res., 5:361-397, 2004.
    • (2004) J. Mach. Learn. Res. , vol.5 , pp. 361-397
    • Lewis, D.D.1    Yang, Y.2    Rose, T.G.3    Li, F.4
  • 13
    • 0000695404 scopus 로고
    • Information-based objective functions for active data selection
    • D. MacKay. Information-based objective functions for active data selection. Neural Comput., 4(4):590-604, 1992.
    • (1992) Neural Comput. , vol.4 , Issue.4 , pp. 590-604
    • MacKay, D.1
  • 14
    • 0000314722 scopus 로고    scopus 로고
    • Employing EM and pool-based active learning for text classification
    • A. McCallum and K. Nigam. Employing EM and pool-based active learning for text classification. In ICML, 1998.
    • (1998) ICML
    • McCallum, A.1    Nigam, K.2
  • 15
    • 14344265134 scopus 로고    scopus 로고
    • Active learning using pre-clustering
    • H. T. Nguyen and A. Smeulders. Active learning using pre-clustering. In ICML, 2004.
    • (2004) ICML
    • Nguyen, H.T.1    Smeulders, A.2
  • 16
    • 0442319140 scopus 로고    scopus 로고
    • Toward optimal active learning through sampling estimation of error reduction
    • N. Roy and A. McCallum. Toward optimal active learning through sampling estimation of error reduction. In ICML, 2001.
    • (2001) ICML
    • Roy, N.1    McCallum, A.2
  • 18
    • 0042868698 scopus 로고    scopus 로고
    • Support vector machine active learning with applications to text classification
    • S. Tong and D. Koller. Support vector machine active learning with applications to text classification. J. Mach. Learn. Res., 2:45-66, 2002.
    • (2002) J. Mach. Learn. Res. , vol.2 , pp. 45-66
    • Tong, S.1    Koller, D.2
  • 19
    • 85024373635 scopus 로고    scopus 로고
    • A re-examination of text categorization methods
    • Y. Yang and X. Liu. A re-examination of text categorization methods. In SIGIR, 1999.
    • (1999) SIGIR
    • Yang, Y.1    Liu, X.2
  • 20
    • 33749265864 scopus 로고    scopus 로고
    • Active learning via transductive experimental design
    • K. Yu, J. Bi, and V. Tresp. Active learning via transductive experimental design. In ICML, 2006.
    • (2006) ICML
    • Yu, K.1    Bi, J.2    Tresp, V.3
  • 21
    • 57349188463 scopus 로고    scopus 로고
    • Non-greedy active learning for text categorization using convex transductive experimental design
    • K. Yu, S. Zhu, W. Xu, and Y. Gong. Non-greedy active learning for text categorization using convex transductive experimental design. In SIGIR, 2008.
    • (2008) SIGIR
    • Yu, K.1    Zhu, S.2    Xu, W.3    Gong, Y.4
  • 22
    • 1542347782 scopus 로고    scopus 로고
    • Robustness of regularized linear classification methods in text categorization
    • J. Zhang and Y. Yang. Robustness of regularized linear classification methods in text categorization. In SIGIR, 2003.
    • (2003) SIGIR
    • Zhang, J.1    Yang, Y.2
  • 23
    • 77956028074 scopus 로고    scopus 로고
    • Convex experimental design using manifold structure for image retrieval
    • L. Zhang, C. Chen, W. Chen, J. Bu, D. Cai, and X. He. Convex experimental design using manifold structure for image retrieval. In ACM MM, 2009.
    • (2009) ACM MM
    • Zhang, L.1    Chen, C.2    Chen, W.3    Bu, J.4    Cai, D.5    He, X.6
  • 24
    • 0001868572 scopus 로고    scopus 로고
    • Text categorization based on regularized linear classification methods
    • T. Zhang and F. J. Oles. Text categorization based on regularized linear classification methods. Inform. Retrieval, 4(1):5-31, 2001.
    • (2001) Inform. Retrieval , vol.4 , Issue.1 , pp. 5-31
    • Zhang, T.1    Oles, F.J.2
  • 25
    • 14344254639 scopus 로고    scopus 로고
    • Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions
    • X. Zhu, J. Lafferty, and Z. Ghahramani. Combining active learning and semi-supervised learning using gaussian fields and harmonic functions. In ICML Workshop, 2003.
    • (2003) ICML Workshop
    • Zhu, X.1    Lafferty, J.2    Ghahramani, Z.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.