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Volumn , Issue , 1998, Pages 500-506

Linear concepts and hidden variables: An empirical study

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION TASKS; EMPIRICAL STUDIES; HIDDEN VARIABLE; LEARNING TECHNIQUES; LINEAR CLASSIFIERS; LINEAR FUNCTIONS; OBSERVED VALUES; PROBABILISTIC MODELING;

EID: 84898974674     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (1)

References (7)
  • 1
    • 0030819669 scopus 로고    scopus 로고
    • Empirical support for winnow and weighted majority based algorithms: Results on a calendar scheduling domain
    • Blu97
    • [Blu97] A. Blum. Empirical support for winnow and weighted majority based algorithms: results on a calendar scheduling domain. Machine Learning, 26:1-19, 1997.
    • (1997) Machine Learning , vol.26 , pp. 1-19
    • Blum, A.1
  • 2
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the EM algorithm
    • DLR77
    • [DLR77] A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from incomplete data via the EM algorithm. Royal Statistical Society By 39:1-38, 1977.
    • (1977) Royal Statistical Society by , vol.39 , pp. 1-38
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
  • 5
    • 34250091945 scopus 로고
    • Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm
    • Lit88
    • [Lit88] N. Littlestone. Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm. Machine Learning, 2:285-318, 1988.
    • (1988) Machine Learning , vol.2 , pp. 285-318
    • Littlestone, N.1
  • 6
    • 0000511449 scopus 로고
    • Redundant noisy attributes, attribute errors, and linear threshold learning using Winnow
    • Lit91, San Mateo, CA, Morgan Kaufmann
    • [Lit91] N. Littlestone. Redundant noisy attributes, attribute errors, and linear threshold learning using Winnow. In Proc. 4th Annu. Workshop on Comput. Learning Theory, pages 147-156, San Mateo, CA, 1991. Morgan Kaufmann.
    • (1991) Proc. 4th Annu. Workshop on Comput. Learning Theory , pp. 147-156
    • Littlestone, N.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.