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Volumn 1418, Issue , 1998, Pages 411-425

Relational concepts and the fourier transform: An empirical study

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE;

EID: 84958606722     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-64575-6_67     Document Type: Conference Paper
Times cited : (2)

References (18)
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    • (1988) Complexity in Information Theory, Chapter VI , pp. 115-131
    • Abu-Mostafa, Y.S.1
  • 3
    • 0015987426 scopus 로고
    • Prediction of protein conformation
    • Peter Y. Chou and Gerald D. Fasman. Prediction of protein conformation. Biochemistry, 13(2):222-245, 1974.
    • (1974) Biochemistry , vol.13 , Issue.2 , pp. 222-245
    • Chou, P.Y.1    Fasman, G.D.2
  • 6
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    • Learning boolean functions via the fourier transform
    • V. P. Roychodhury, K-Y. Siu, and A. Orlitsky, editors, Kluwer Academic Publishers
    • Yishay Mansour. Learning boolean functions via the fourier transform. In V. P. Roychodhury, K-Y. Siu, and A. Orlitsky, editors, Advances in Neural Computation, pages 151-155. Kluwer Academic Publishers, 1994.
    • (1994) Advances in Neural Computation , pp. 151-155
    • Mansour, Y.1
  • 8
    • 0003682772 scopus 로고
    • Technical Report CBM-TR-117, Computer Science Department, Rutgers University, New Brunswick, NJ 08903
    • Tom M. Mitchell. The need for biases in learning generalizations. Technical Report CBM-TR-117, Computer Science Department, Rutgers University, New Brunswick, NJ 08903, May 1980.
    • (1980) The Need for Biases in Learning Generalizations
    • Mitchell, T.M.1
  • 9
    • 0025389210 scopus 로고
    • Boolean feature discovery in empirical learning
    • Giulia Pagallo and David Haussler. Boolean feature discovery in empirical learning. Machine Learning, 5:71-99, 1990.
    • (1990) Machine Learning , vol.5 , pp. 71-99
    • Pagallo, G.1    Haussler, D.2
  • 10
    • 0008814745 scopus 로고
    • Using multidimensional projection to find relations
    • Morgan Kaufmann Publishers, Inc
    • Eduardo Perez and Larry A. Rendell. Using multidimensional projection to find relations. In Proc. of the 12th Int. Conf. on Machine Learning, pages 447-455. Morgan Kaufmann Publishers, Inc., 1995.
    • (1995) Proc. of the 12Th Int. Conf. on Machine Learning , pp. 447-455
    • Perez, E.1    Rendell, L.A.2
  • 11
    • 4243730545 scopus 로고    scopus 로고
    • Learning despite concept variation by finding structure in attribute-based data
    • Morgan Kaufmann Publishers, Inc
    • Eduardo Perez and Larry A. Rendell. Learning despite concept variation by finding structure in attribute-based data. In Proc. of the 13th Int. Conf. on Machine Learning, pages 391-399. Morgan Kaufmann Publishers, Inc., 1996.
    • (1996) Proc. of the 13Th Int. Conf. on Machine Learning , pp. 391-399
    • Perez, E.1    Rendell, L.A.2
  • 14
    • 0001594860 scopus 로고
    • A general framework for induction and a study of selective induction
    • Larry Rendell. A general framework for induction and a study of selective induction. Machine Learning, 1(2): 177–226, 1986.
    • (1986) Machine Learning , vol.1 , Issue.2 , pp. 177-226
    • Rendell, L.1
  • 15
    • 0000686085 scopus 로고
    • Learning hard concepts through constructive induction: Framework and rationale
    • Larry A. Rendell and Raj Seshu. Learning hard concepts through constructive induction: Framework and rationale. Computational Intelligence, 6:247-270, 1990.
    • (1990) Computational Intelligence , vol.6 , pp. 247-270
    • Rendell, L.A.1    Seshu, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.