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Volumn 55, Issue 1, 1997, Pages 161-170

Approximation and Learning of Convex Superpositions

Author keywords

[No Author keywords available]

Indexed keywords

FUNCTIONS; LEARNING SYSTEMS; MATHEMATICAL TECHNIQUES; NEURAL NETWORKS;

EID: 0031212925     PISSN: 00220000     EISSN: None     Source Type: Journal    
DOI: 10.1006/jcss.1997.1506     Document Type: Article
Times cited : (31)

References (21)
  • 3
    • 0027599793 scopus 로고
    • Universal approximation bounds for superpositions of a sigmoidal function
    • May
    • A. Barron, Universal approximation bounds for superpositions of a sigmoidal function, IEEE Trans. Inform. Theory 39, No. 3 (May 1993), 930-945.
    • (1993) IEEE Trans. Inform. Theory , vol.39 , Issue.3 , pp. 930-945
    • Barron, A.1
  • 5
    • 0001160588 scopus 로고
    • What size net gives valide generalization?
    • E. B. Baum and D. Haussler, What size net gives valide generalization?, Neural Comput. 1 (1989), 151-160.
    • (1989) Neural Comput. , vol.1 , pp. 151-160
    • Baum, E.B.1    Haussler, D.2
  • 8
    • 0000421687 scopus 로고
    • Central limit theorems for empirical measures
    • R. M. Dudley, Central limit theorems for empirical measures, Ann. Probab. 6, No. 6 (1978), 899-929.
    • (1978) Ann. Probab. , vol.6 , Issue.6 , pp. 899-929
    • Dudley, R.M.1
  • 9
    • 0001605679 scopus 로고
    • Universal Donsker classes and metric entropy
    • R. M. Dudley, Universal Donsker classes and metric entropy, Ann. Probab. 15, No. 4 (1987), 1306-1326.
    • (1987) Ann. Probab. , vol.15 , Issue.4 , pp. 1306-1326
    • Dudley, R.M.1
  • 12
    • 0002192516 scopus 로고
    • Decision theoretic generalizations of the PAC model for neural nets and other learning applications
    • D. Haussler, Decision theoretic generalizations of the PAC model for neural nets and other learning applications, Inform. and Comput. 100 (1992), 78-150.
    • (1992) Inform. and Comput. , vol.100 , pp. 78-150
    • Haussler, D.1
  • 13
    • 0028460231 scopus 로고
    • Efficient distribution-free learning of probabilistic concepts
    • M. Kearns and R. Schapire, Efficient distribution-free learning of probabilistic concepts, J. Comput. System Sci. 48, No. 3 (1994), 464-497.
    • (1994) J. Comput. System Sci. , vol.48 , Issue.3 , pp. 464-497
    • Kearns, M.1    Schapire, R.2
  • 14
    • 84963049054 scopus 로고
    • Vapnik-Chervonenkis classes of definable sets
    • M. Laskowski, Vapnik-Chervonenkis classes of definable sets, J. London Math. Soc. 45, No. 2 (1992), 377-384.
    • (1992) J. London Math. Soc. , vol.45 , Issue.2 , pp. 377-384
    • Laskowski, M.1
  • 16
    • 0002361040 scopus 로고
    • Discrepancy and approximation for bounded VC-dimension
    • J. Matousek, E. Welzl, and L. Wernisch, Discrepancy and approximation for bounded VC-dimension, Combinatorica 13, No. 4 (1993), 455-466.
    • (1993) Combinatorica , vol.13 , Issue.4 , pp. 455-466
    • Matousek, J.1    Welzl, E.2    Wernisch, L.3
  • 17
    • 0000579826 scopus 로고
    • U-processes: Rates of convergences
    • D. Nolan and D. Pollard, U-processes: Rates of convergences, Ann. Statist. 15, No. 2 (1987), 780-799.
    • (1987) Ann. Statist. , vol.15 , Issue.2 , pp. 780-799
    • Nolan, D.1    Pollard, D.2
  • 18
    • 0004206815 scopus 로고
    • Van Nostrand Mathematical Studies, Van Nostrand, New York
    • R. Phelps, "Lectures on Choquet's Theorem," Van Nostrand Mathematical Studies, Van Nostrand, New York, 1966.
    • (1966) Lectures on Choquet's Theorem
    • Phelps, R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.