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Volumn 8, Issue 4, 2014, Pages

Random projections for linear support vector machines

Author keywords

Classification; dimensionality reduction; support vector machines

Indexed keywords

CLASSIFICATION (OF INFORMATION); DIMENSIONALITY REDUCTION; MATRIX ALGEBRA;

EID: 84908246259     PISSN: 15564681     EISSN: 1556472X     Source Type: Journal    
DOI: 10.1145/2641760     Document Type: Conference Paper
Times cited : (44)

References (32)
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  • 8
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    • C.-C. Chang and C.-J. Lin. 2011. LIBSVM: A library for support vector machines. ACMTransactions on Intelligent Systems and Technology 2, 3 (2011), 27:1-27:27. Software available at http://www.csie.ntu.edu.tw/?cjlin/libsvm.
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    • Chang, C.-C.1    Lin, C.-J.2
  • 10
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    • On the learnability and design of output codes for multi-class problems
    • K. Crammer and Y. Singer. 2000. On the learnability and design of output codes for multi-class problems. In Computational Learning Theory. 35-46.
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    • Crammer, K.1    Singer, Y.2
  • 12
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    • An elementary proof of a theorem of johnson and lindenstrauss
    • 2003
    • S. Dasgupta,A. Gupta 2003. An elementary proof of a theorem of Johnson and Lindenstrauss Random Structures and Algorithms 22, 1, 2003, 60-65.
    • (2003) Random Structures and Algorithms , vol.22 , Issue.1 , pp. 60-65
    • Dasgupta, S.1    Gupta, A.2
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    • Paschou, P.1    Lewis, J.2    Javed, A.3    Drineas, P.4
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    • On the uniform convergence of relative frequencies of events to their probabilities
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.