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Volumn 3, Issue , 2009, Pages 1212-1223

Efficient multiplicative updates for support vector machines

Author keywords

[No Author keywords available]

Indexed keywords

ASYMPTOTIC CONVERGENCE; CLASSIFICATION PERFORMANCE; DATA SETS; KERNEL ADATRON ALGORITHMS; LEARNING RATES; MATRIX FACTORIZATIONS; MULTIPLICATIVE UPDATES; NATURAL EXTENSION; NONNEGATIVE MATRIX FACTORIZATION; OBJECTIVE FUNCTIONS; PARAMETER SETTING; QUADRATIC PROGRAMMING PROBLEMS; RAPID CONVERGENCE; SOFT MARGINS; TIGHT BOUND;

EID: 73449144120     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (4)

References (18)
  • 1
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    • Y. Weiss, B. Schlkopf, and J. Piatt, editors, MIT Press, Cambridge, MA
    • Inderjit Dhillon and Suvrit Sra. Generalized nonnegative matrix approximations with Bregman divergences. In Y. Weiss, B. Schlkopf, and J. Piatt, editors, Ad-vances in Neural Information Processing Systems 18, pages 283-290. MIT Press, Cambridge, MA, 2006.
    • (2006) Ad-vances in Neural Information Processing Systems 18 , pp. 283-290
    • Dhillon, I.1    Sra, S.2
  • 2
    • 47649090653 scopus 로고    scopus 로고
    • Convex and semi-nonnegative matrix factorizations
    • 60428
    • Chris Ding, Tao Li, and Michael I. Jordan. Convex and semi-nonnegative matrix factorizations. LBNL Tech Report 60428, 2006.
    • (2006) LBNL Tech Report
    • Ding, C.1    Li, T.2    Jordan, M.I.3
  • 4
    • 33646153072 scopus 로고    scopus 로고
    • Sequential coordinate-wise algorithm for the non-negative least squares problem
    • V. Franc, V. Hlavac, and M. Navara. Sequential coordinate-wise algorithm for the non-negative least squares problem. In Computer Analysis of Images and Patterns, page 407, 2005.
    • (2005) Computer Analysis of Images and Patterns , pp. 407
    • Franc, V.1    Hlavac, V.2    Navara, M.3
  • 5
    • 0000897328 scopus 로고    scopus 로고
    • The Kernel-Adatron algorithm: A fast and simple learning procedure for support vector machines
    • Morgan Kaufmann, San Francisco, CA
    • Thilo-Thomas Frieß, Nello Cristianini, and Colin Campbell. The Kernel-Adatron algorithm: a fast and simple learning procedure for support vector machines. In Proc. 15th International Conf. on Machine Learning, pages 188-196. Morgan Kaufmann, San Francisco, CA, 1998.
    • (1998) Proc. 15th International Conf. on Machine Learning , pp. 188-196
    • Frieß, T.-T.1    Cristianini, N.2    Campbell, C.3
  • 6
    • 33646193503 scopus 로고    scopus 로고
    • On the equality of kernel adatron and sequential minimal optimization in classification and regression tasks and alike algorithms for kernel machines
    • Vojislav Kecman, Michael Vogt, and Te Ming Huang. On the equality of kernel adatron and sequential minimal optimization in classification and regression tasks and alike algorithms for kernel machines. In ESANN, pages 215-222, 2003.
    • (2003) ESANN , pp. 215-222
    • Kecman, V.1    Vogt, M.2    Te, M.3
  • 8
    • 0001093042 scopus 로고    scopus 로고
    • Algorithms for non-negative matrix factorization
    • Daniel D. Lee and Sebastian H. Seung. Algorithms for non-negative matrix factorization. In NIPS, pages 556-562, 2000.
    • (2000) NIPS , pp. 556-562
    • Lee, D.D.1    Seung, S.H.2
  • 9
    • 35548969471 scopus 로고    scopus 로고
    • Projected gradient methods for nonnegative matrix factorization
    • October
    • Chih-Jen Lin. Projected gradient methods for nonnegative matrix factorization. Neural Comp., 19(10):2756-2779, October 2007.
    • (2007) Neural Comp , vol.19 , Issue.10 , pp. 2756-2779
    • Lin, C.-J.1
  • 17
    • 84899026127 scopus 로고    scopus 로고
    • Multiplicative updates for nonnegative quadratic programming in support vector machines
    • Sebastian Thrun Suzanna Becker and Klaus Obermayer, editors, Cambridge, MA, MIT Press
    • Fei Sha, Lawrence K. Saul, and Daniel D. Lee. Multiplicative updates for nonnegative quadratic programming in support vector machines. In Sebastian Thrun Suzanna Becker and Klaus Obermayer, editors, Advances in Neural Information Processing Systems 15, Cambridge, MA, 2003. MIT Press.
    • (2003) Advances in Neural Information Processing Systems 15
    • Sha, F.1    Saul, L.K.2    Lee, D.D.3
  • 18
    • 47749123490 scopus 로고    scopus 로고
    • Fast nonnegative matrix factorization algorithms using projected gradient approaches for large-scale problems
    • Rafal Zdunek and Andrzej Cichocki. Fast nonnegative matrix factorization algorithms using projected gradient approaches for large-scale problems. Computational Intelligence and Neuroscience, page 13, 2008.
    • (2008) Computational Intelligence and Neuroscience , pp. 13
    • Zdunek, R.1    Cichocki, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.