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Volumn 1, Issue , 2003, Pages 559-564

A Dual-Phase Technique for Pruning Constructive Networks

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; COMPUTER SIMULATION; CORRELATION METHODS; ERROR ANALYSIS; OPTIMIZATION; PROBLEM SOLVING; TOPOLOGY; VECTORS;

EID: 0141573281     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (11)

References (15)
  • 3
    • 0000900876 scopus 로고
    • Skeletonization: A technique for trimming the fat from a network via relevance assessment
    • Morgan Kaufmann
    • Mozer, MC & Smolensky, P. (1988). Skeletonization: A technique for trimming the fat from a network via relevance assessment. Advances in Neural Information Processing Systems, 1. Morgan Kaufmann. 107-115.
    • (1988) Advances in Neural Information Processing Systems , vol.1 , pp. 107-115
    • Mozer, M.C.1    Smolensky, P.2
  • 5
    • 0000703707 scopus 로고
    • Structural adaptation and generalization in supervised feed-forward networks
    • Ghosh, J., Turner, K. (1994). Structural adaptation and generalization in supervised feed-forward networks. Neural Networks, 1, pp. 431-458.
    • (1994) Neural Networks , vol.1 , pp. 431-458
    • Ghosh, J.1    Turner, K.2
  • 9
    • 0036825537 scopus 로고    scopus 로고
    • Evaluation of constructive neural networks with cascaded architecture
    • Lahnajarvi, J.T., Lehtokangas, M.I., Saarinen, J.P.P. (2002). Evaluation of constructive neural networks with cascaded architecture. Neurocomputing, 48, 573-607.
    • (2002) Neurocomputing , vol.48 , pp. 573-607
    • Lahnajarvi, J.T.1    Lehtokangas, M.I.2    Saarinen, J.P.P.3
  • 11
    • 0035536720 scopus 로고    scopus 로고
    • Knowledge-based cascade correlation: Using knowledge to speed learning
    • Shultz, T. R., & Rivest, F. (2001). Knowledge-based cascade correlation: Using knowledge to speed learning. Connection Science, 13, 43-72.
    • (2001) Connection Science , vol.13 , pp. 43-72
    • Shultz, T.R.1    Rivest, F.2
  • 15
    • 0004114283 scopus 로고
    • PROBEN1 - A set of benchmarks and benchmarking rules for neural network training algorithms
    • Fakultät für Informatik, Universität Karlsruhe
    • Prechelt, L. (1994). PROBEN1 - A set of benchmarks and benchmarking rules for neural network training algorithms. Technical report 21/94, Fakultät für Informatik, Universität Karlsruhe.
    • (1994) Technical Report , vol.21 , Issue.94
    • Prechelt, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.