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Volumn 7700 LECTURE NO, Issue , 2012, Pages 53-67

Early stopping - But when?

Author keywords

[No Author keywords available]

Indexed keywords

NETWORK ARCHITECTURE;

EID: 84872548900     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-35289-8_5     Document Type: Article
Times cited : (1364)

References (25)
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    • Baldi, P., Chauvin, Y.: Temporal evolution of generalization during learning in linear networks. Neural Computation 3, 589-603 (1991)
    • (1991) Neural Computation , vol.3 , pp. 589-603
    • Baldi, P.1    Chauvin, Y.2
  • 6
    • 0003578240 scopus 로고
    • An empirical study of learning speed in back-propagation networks
    • Carnegie Mellon University, Pittsburgh, PA September
    • Fahlman, S.E.: An empirical study of learning speed in back-propagation networks. Technical Report CMU-CS-88-162, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA (September 1988)
    • (1988) Technical Report CMU-CS-88-162, School of Computer Science
    • Fahlman, S.E.1
  • 9
    • 0027294340 scopus 로고
    • Improving model selection by nonconvergent methods
    • Finnoff, W., Hergert, F., Zimmermann, H.G.: Improving model selection by nonconvergent methods. Neural Networks 6, 771-783 (1993) (Pubitemid 23713282)
    • (1993) Neural Networks , vol.6 , Issue.6 , pp. 771-783
    • Finnoff, W.1    Hergert, F.2    Zimmermann, H.G.3
  • 18
    • 0001765492 scopus 로고
    • Simplifying neural networks by soft weight-sharing
    • Nowlan, S.J., Hinton, G.E.: Simplifying neural networks by soft weight-sharing. Neural Computation 4(4), 473-493 (1992)
    • (1992) Neural Computation , vol.4 , Issue.4 , pp. 473-493
    • Nowlan, S.J.1    Hinton, G.E.2
  • 19
    • 0004114283 scopus 로고
    • Proben1 - A set of benchmarks and benchmarking rules for neural network training algorithms
    • Universitat Karlsruhe, Germany, Anonymous, September ftp://pub/papers/ techreports/1994/1994-21.ps.gz on, ftp.ira.uka.de
    • Prechelt, L.: PROBEN1 - A set of benchmarks and benchmarking rules for neural network training algorithms. Technical Report 21/94, Fakultat fur Informatik, Universitat Karlsruhe, Germany, Anonymous, ftp://pub/papers/ techreports/1994/1994-21.ps.gz on, ftp.ira.uka.de (September 1994)
    • (1994) Technical Report 21/94, Fakultat fur Informatik
    • Prechelt, L.1
  • 20
  • 21
    • 84943274699 scopus 로고
    • A direct adaptive method for faster backpropagation learning: The RPROP algorithm
    • San Francisco, CA April
    • Riedmiller, M., Braun, H.: A direct adaptive method for faster backpropagation learning: The RPROP algorithm. In: Proc. of the IEEE Intl. Conf. on Neural Networks, San Francisco, CA, pp. 586-591 (April 1993)
    • (1993) Proc. of the IEEE Intl. Conf. on Neural Networks , pp. 586-591
    • Riedmiller, M.1    Braun, H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.