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Volumn 2003-January, Issue , 2003, Pages 499-508

Online SVM learning: From classification to data description and back

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA DESCRIPTION; DIGITAL STORAGE; IMAGE SEGMENTATION; LEARNING ALGORITHMS; SIGNAL PROCESSING;

EID: 79960753941     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NNSP.2003.1318049     Document Type: Conference Paper
Times cited : (106)

References (20)
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    • (2002) Advances in Neural Inf. Proc. Systems (NIPS Ol , vol.14 , pp. 157-164
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    • Svmtorch: Support vector machines for largescale regression problems
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    • Collobert, R.1    Bengio, S.2
  • 6
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    • Making large-scale SVM learning practical
    • B. Scbolkopf, C. Burges and A. Smola (eds. Cambridge, MA: MIT Press
    • T. Joachims, "Making Large-scale SVM Learning Practical," in B. Scbolkopf, C. Burges and A. Smola (eds.), Advances in Kernel Methods-Support Vector Learning, Cambridge, MA: MIT Press, 1999, pp. 161t184.
    • (1999) Advances in Kernel Methods-Support Vector Learning , pp. 161t184
    • Joachims, T.1
  • 8
    • 0036158636 scopus 로고    scopus 로고
    • Feasible direction decomposition algorithms for training support vector machines
    • P. Laskov, "Feasible direction decomposition algorithms for training support vector machines," Machine Learning, vol. 46, pp. 315-349, 2002.
    • (2002) Machine Learning , vol.46 , pp. 315-349
    • Laskov, P.1
  • 11
    • 0030130884 scopus 로고    scopus 로고
    • Network contraints and multi-objective optimization for one-class classification
    • hI. Moya and D. Hush, "Network contraints and multi-objective optimization for one-class classification," Neural Networks, vol. 9, no. 3, pp. 463-474, 1996.
    • (1996) Neural Networks , vol.9 , Issue.3 , pp. 463-474
    • Moya, H.1    Hush, D.2
  • 12
    • 84958962423 scopus 로고    scopus 로고
    • Incremental support vector machine learning: A local approach
    • L. Ralaivola and F. D'Alcha Buc, "Incremental Support Vector Machine Learning: A Local Approach," Lecture Notes in Computer Science, vol. 2130, pp. 322-329, 2001.
    • (2001) Lecture Notes in Computer Science , vol.2130 , pp. 322-329
    • Ralaivola, L.1    D'Alcha Buc, F.2
  • 17
    • 0002493574 scopus 로고    scopus 로고
    • Sparse greedy matrix approximation for machine learning
    • P. Langley (ed. San Francisco: Morgan Kaufmann
    • A. Smola and B. Scholkopf, "Sparse greedy matrix approximation for machine learning," in P. Langley (ed.), Proc. ICML'OO, San Francisco: Morgan Kaufmann, 2000, pp. 911-918.
    • (2000) Proc. ICML'OO , pp. 911-918
    • Smola, A.1    Scholkopf, B.2
  • 18
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    • Incremental learning with support vector machines
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  • 19
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    • Uniform object generation for optimizing one-class classifiers
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    • Tax, D.1    Duin, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.