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Volumn 29, Issue 2-3, 1997, Pages 165-180

The Sample Complexity of Learning Fixed-Structure Bayesian Networks

Author keywords

Bayesian networks; PAC learning; Sample complexity

Indexed keywords

APPROXIMATION THEORY; COMPUTATIONAL COMPLEXITY; PROBABILITY;

EID: 0031269467     PISSN: 08856125     EISSN: None     Source Type: Journal    
DOI: 10.1023/a:1007417612269     Document Type: Article
Times cited : (54)

References (10)
  • 1
    • 2442440275 scopus 로고
    • Polynomial learnability of probabilistic concepts with respect to the Kullback-Leibler divergence
    • San Mateo, CA: Morgan Kaufmann
    • Abe, N., Takeuchi, J., & Warmuth M. (1990). Polynomial learnability of probabilistic concepts with respect to the Kullback-Leibler divergence. ACM Conference on Computational Learning Theory. San Mateo, CA: Morgan Kaufmann.
    • (1990) ACM Conference on Computational Learning Theory
    • Abe, N.1    Takeuchi, J.2    Warmuth, M.3
  • 3
    • 0000421687 scopus 로고
    • Central limit theorems for empirical measures
    • Dudley, R. M. (1978). Central limit theorems for empirical measures. Annals of Probability, 6, 899-929.
    • (1978) Annals of Probability , vol.6 , pp. 899-929
    • Dudley, R.M.1
  • 5
    • 0002192516 scopus 로고
    • Decision-theoretic generalizations of the PAC model for neural net and other learning applications
    • Haussler, D. (1992). Decision-theoretic generalizations of the PAC model for neural net and other learning applications. Information and Computation, 100, 78-150.
    • (1992) Information and Computation , vol.100 , pp. 78-150
    • Haussler, D.1
  • 9
    • 0021518106 scopus 로고
    • A theory of the learnable
    • Valiant, L. (1984). A theory of the learnable. Communications of the ACM, 27, 1134-1142.
    • (1984) Communications of the ACM , vol.27 , pp. 1134-1142
    • Valiant, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.