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Volumn , Issue , 2010, Pages 61-66

Searching for minimal neural networks in fourier space

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEX NETWORKS; ENCODING (SYMBOLS); FREQUENCY DOMAIN ANALYSIS; NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 77954099341     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.2991/agi.2010.28     Document Type: Conference Paper
Times cited : (13)

References (16)
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    • Jason Gauci and Kenneth Stanley. Generating large-scale neural networks through discovering geometric regularities. In Proceedings of the Conference on Genetic and Evolutionary Computation, pages 997-1004, New York, NY, USA, 2007. ACM.
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    • Gauci, J.1    Stanley, K.2
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    • Three approaches to the quantitative definition of information
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    • Kolmogorov, A.N.1
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    • Universal sequential search problems
    • L. A. Levin. Universal sequential search problems. Problems of Information Transmission, 9(3):265-266, 1973.
    • (1973) Problems of Information Transmission , vol.9 , Issue.3 , pp. 265-266
    • Levin, L.A.1
  • 8
    • 1542329420 scopus 로고
    • Genetic set recombination and its application to neural network topology optimisation
    • Nicholas J. Radcliffe. Genetic set recombination and its application to neural network topology optimisation. Neural Computing and Applications, 1(1):67-90, 1993.
    • (1993) Neural Computing and Applications , vol.1 , Issue.1 , pp. 67-90
    • Radcliffe, N.J.1
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    • Rissanen, J.1
  • 10
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    • Discovering solutions with low Kolmogorov complexity and high generalization capability
    • A. Prieditis and S. Russell, editors, Morgan Kaufmann Publishers, San Francisco, CA
    • J. Schmidhuber. Discovering solutions with low Kolmogorov complexity and high generalization capability. In A. Prieditis and S. Russell, editors, Proceedings of the Twelfth International Conference on Machine Learning (ICML), pages 488-496. Morgan Kaufmann Publishers, San Francisco, CA, 1995.
    • (1995) Proceedings of the Twelfth International Conference on Machine Learning (ICML) , pp. 488-496
    • Schmidhuber, J.1
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    • 0031194381 scopus 로고    scopus 로고
    • Discovering neural nets with low Kolmogorov complexity and high generalization capability
    • J. Schmidhuber. Discovering neural nets with low Kolmogorov complexity and high generalization capability. Neural Networks, 10(5):857-873, 1997.
    • (1997) Neural Networks , vol.10 , Issue.5 , pp. 857-873
    • Schmidhuber, J.1
  • 12
    • 84937439050 scopus 로고    scopus 로고
    • The speed prior: A new simplicity measure yielding near-optimal computable predictions
    • J. Kivinen and R. H. Sloan, editors, Lecture Notes in Artificial Intelligence, Springer, Sydney, Australia
    • J. Schmidhuber. The Speed Prior: a new simplicity measure yielding near-optimal computable predictions. In J. Kivinen and R. H. Sloan, editors, Proceedings of the 15th Annual Conference on Computational Learning Theory (COLT 2002), Lecture Notes in Artificial Intelligence, pages 216-228. Springer, Sydney, Australia, 2002.
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    • A formal theory of inductive inference. Part I
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    • An information theoretic measure for classification
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    • Evolving neural network controllers for unstable systems
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.