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Volumn , Issue , 1995, Pages 197-203

Neural Networks with Quadratic VC Dimension

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVATION FUNCTIONS; GENERALISATION; NEURAL-NETWORKS; NUMBER OF SAMPLES; VC-DIMENSION;

EID: 85156276965     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (23)

References (14)
  • 2
    • 0001160588 scopus 로고
    • What size net gives valid generalization?
    • E. B. BAUM and D. HAUSSLER (1989) What size net gives valid generalization?, Neural Computation 1, pp. 151-160.
    • (1989) Neural Computation , vol.1 , pp. 151-160
    • BAUM, E. B.1    HAUSSLER, D.2
  • 3
    • 84968516134 scopus 로고
    • On the theory of computation and complexity over the real numbers: NP-completeness, recursive functions and universal machines
    • L. BLUM, M. SHUB and S. SMALE (1989) On the theory of computation and complexity over the real numbers: NP-completeness, recursive functions and universal machines, Bulletin of the AMS 21, pp. 1-46.
    • (1989) Bulletin of the AMS , vol.21 , pp. 1-46
    • BLUM, L.1    SHUB, M.2    SMALE, S.3
  • 5
    • 0013995259 scopus 로고
    • Capacity problems for linear machines
    • L. Kanal ed., Thompson Book Co
    • T. M. COVER (1988) Capacity problems for linear machines, in: Pattern Recognition, L. Kanal ed., Thompson Book Co., pp. 283-289.
    • (1988) Pattern Recognition , pp. 283-289
    • COVER, T. M.1
  • 6
    • 0029256399 scopus 로고
    • Bounding the Vapnik-Chervonenkis dimension of concept classes parametrized by real numbers
    • P. GOLDBERG and M. JERRUM (1995) Bounding the Vapnik-Chervonenkis dimension of concept classes parametrized by real numbers, Machine Learning 18, pp. 131-148.
    • (1995) Machine Learning , vol.18 , pp. 131-148
    • GOLDBERG, P.1    JERRUM, M.2
  • 8
    • 0027224339 scopus 로고
    • Bounds for the computational power and learning complexity of analog neural nets
    • W. MAASS (1993) Bounds for the computational power and learning complexity of analog neural nets, in Proc. of the 25th ACM Symp. Theory of Computing, pp. 335-344.
    • (1993) Proc. of the 25th ACM Symp. Theory of Computing , pp. 335-344
    • MAASS, W.1
  • 9
    • 0011900550 scopus 로고
    • Perspectives of current research about the complexity of learning in neural nets
    • P. Roychowd-hury, K. Y. Siu, and A. Orlitsky, editors, Kluwer, Boston
    • W. MAASS (1994) Perspectives of current research about the complexity of learning in neural nets, in Theoretical Advances in Neural Computation and Learning, V. P. Roychowd-hury, K. Y. Siu, and A. Orlitsky, editors, Kluwer, Boston, pp. 295-336.
    • (1994) Theoretical Advances in Neural Computation and Learning , pp. 295-336
    • MAASS, W.1
  • 11
    • 0343295539 scopus 로고
    • Sigmoids distinguish better than Heavisides
    • E. D. SONTAG (1989) Sigmoids distinguish better than Heavisides, Neural Computation 1, pp. 470-472.
    • (1989) Neural Computation , vol.1 , pp. 470-472
    • SONTAG, E. D.1
  • 12
    • 0026904597 scopus 로고
    • Feedforward nets for interpolation and classification
    • E. D. SONTAG (1992) Feedforward nets for interpolation and classification, J. Comp. Syst. Sci 45, pp. 20-48.
    • (1992) J. Comp. Syst. Sci , vol.45 , pp. 20-48
    • SONTAG, E. D.1
  • 13
    • 0021518106 scopus 로고
    • A theory of the learnable
    • L. G. VALIANT (1984) A theory of the learnable, Comm. of the ACM 27, pp. 1134-1142
    • (1984) Comm. of the ACM , vol.27 , pp. 1134-1142
    • VALIANT, L. G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.