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Volumn , Issue , 2006, Pages 3196-3203

Dynamic hyperparameter scaling method for LVQ algorithms

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); LEARNING SYSTEMS; ONLINE SYSTEMS; PARAMETER ESTIMATION; VECTOR QUANTIZATION;

EID: 40649125311     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (13)

References (20)
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    • R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification, 2nd ed. New York: Sohn Wiley & Sons, 2001.
  • 5
    • 0028531044 scopus 로고
    • Prototype-based minimum classification error/generalized probabilistic descent training for various speech units
    • E. McDermott and S. Katagiri, "Prototype-based minimum classification error/generalized probabilistic descent training for various speech units," Computer Speech and Language, vol. 8, no. 4. pp. 351-368, 1994.
    • (1994) Computer Speech and Language , vol.8 , Issue.4 , pp. 351-368
    • McDermott, E.1    Katagiri, S.2
  • 8
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    • T. Kohonen, Learning vector quantization, Helsinki Univ. of Tech., Otaniemi, Tech. Rep., 1986.
    • T. Kohonen, "Learning vector quantization," Helsinki Univ. of Tech., Otaniemi, Tech. Rep., 1986.
  • 9
    • 40649093525 scopus 로고    scopus 로고
    • N. N. R. Centre, Bibliography on the Self-Oiganizing Map (SOM) and Learning Vector Quantization (LVQ), Helsinki Univ. of Tech., 2003, http://liinwww.ira.uka.de/bibliography/Neural/SOM.LVQ.html.
    • N. N. R. Centre, Bibliography on the Self-Oiganizing Map (SOM) and Learning Vector Quantization (LVQ), Helsinki Univ. of Tech., 2003, http://liinwww.ira.uka.de/bibliography/Neural/SOM.LVQ.html.
  • 10
    • 85156210800 scopus 로고    scopus 로고
    • Generalized learning vector quantization
    • D. Touretzky, M. Mozer, and M. Ha'sselmo, Eds. MIT Press
    • A. Sato and K. Yamada. "Generalized learning vector quantization," in Advances in Neural Information Processing Systems 8, D. Touretzky, M. Mozer, and M. Ha'sselmo, Eds. MIT Press, 1996, pp. 423-429.
    • (1996) Advances in Neural Information Processing Systems 8 , pp. 423-429
    • Sato, A.1    Yamada, K.2
  • 13
    • 0038159964 scopus 로고    scopus 로고
    • Soft learning vector quantization
    • S. Seo and K. Obermayer, "Soft learning vector quantization," Neural Computation, vol. 15. pp. 1589-1604, 2003.
    • (2003) Neural Computation , vol.15 , pp. 1589-1604
    • Seo, S.1    Obermayer, K.2
  • 14
    • 0034241361 scopus 로고    scopus 로고
    • Gradient-based optimization of hyperparameters
    • Y. Bengio. "Gradient-based optimization of hyperparameters," Neural Computation, vol. 12, no. 8. pp. 1889-1900, 2000.
    • (2000) Neural Computation , vol.12 , Issue.8 , pp. 1889-1900
    • Bengio, Y.1
  • 16
    • 0000016172 scopus 로고
    • A stochastic approximation method
    • H. Robbins and S. Monro, "A stochastic approximation method," Ann. Math. Stat., vol. 22, pp. 400-407, 1951.
    • (1951) Ann. Math. Stat , vol.22 , pp. 400-407
    • Robbins, H.1    Monro, S.2
  • 17
    • 0000787409 scopus 로고    scopus 로고
    • Phase transduction in stochastic self-organizing maps
    • T. Graepel, M. Burger, and K. Obermayer. "Phase transduction in stochastic self-organizing maps," Physical Review E., vol. 56, pp. 3876-3890, 1997.
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    • Graepel, T.1    Burger, M.2    Obermayer, K.3
  • 18
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    • A global optimization technique for statistical classifier design
    • D. Miller, A. V. Rao. K. Rose, and A. Gersho, "A global optimization technique for statistical classifier design," IEEE Transactions on Signal Processing, vol. 44, no. 12. pp. 3108-22, 1996.
    • (1996) IEEE Transactions on Signal Processing , vol.44 , Issue.12 , pp. 3108-3122
    • Miller, D.1    Rao, A.V.2    Rose, K.3    Gersho, A.4
  • 19
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    • Online learning and stochastic approximations
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  • 20
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    • Clustering and prototype based classification
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.