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Volumn 2533, Issue , 2002, Pages 83-97

Maximizing agreements and coagnostic learning

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION ALGORITHMS; BOOLEAN ALGEBRA; GEOMETRY;

EID: 4544368467     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-36169-3_9     Document Type: Conference Paper
Times cited : (3)

References (13)
  • 1
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    • The complexity and approximability of finding maximum feasible subsystems of linear relations
    • E. Amaldi and V. Kann, The complexity and approximability of finding maximum feasible subsystems of linear relations, Theoretical Computer Science, 147: 181-210, 1995.
    • (1995) Theoretical Computer Science , vol.147 , pp. 181-210
    • Amaldi, E.1    Kann, V.2
  • 4
    • 29144432674 scopus 로고    scopus 로고
    • Bounds for the Minimum Disagreement Problem with Applications to Learning Theory
    • N. H. Bshouty, L. Burroughs. Bounds for the Minimum Disagreement Problem with Applications to Learning Theory. 15th COLT, 271-286, 2002.
    • (2002) 15Th COLT , pp. 271-286
    • Bshouty, N.H.1    Burroughs, L.2
  • 5
    • 0002544375 scopus 로고    scopus 로고
    • On the difficulty of approximately maximizing agreement
    • S. Ben-David, N. Eiron, P. M. Long. On the difficulty of approximately maximizing agreement. 13th COLT, 266-274, 2000.
    • (2000) 13Th COLT , pp. 266-274
    • Ben-David, S.1    Eiron, N.2    Long, P.M.3
  • 6
    • 0030671781 scopus 로고    scopus 로고
    • Some optimal inapproximability results
    • J. Hastad, Some optimal inapproximability results, 29th STOC, 1-10, 1997.
    • (1997) 29Th STOC , pp. 1-10
    • Hastad, J.1
  • 7
    • 0002192516 scopus 로고
    • Decision theoretic generalizations of the PAC model for neural net and other learning applications. Inform
    • Sept
    • D. Haussler, Decision theoretic generalizations of the PAC model for neural net and other learning applications. Inform. Comput., 100(1):78-150, Sept. 1992.
    • (1992) Comput , vol.100 , Issue.1 , pp. 78-150
    • Haussler, D.1
  • 8
    • 0029255662 scopus 로고
    • Robust trainability of single neurons
    • Klaus-U Höffgen, Hans-U. Simon and Kevin S. Van Horn, Robust trainability of single neurons, JCSS, 50(1): 114-125, 1995.
    • (1995) JCSS , vol.50 , Issue.1 , pp. 114-125
    • Höffgen, K.-U.1    Simon, H.-U.2    Horn, K.S.V.3
  • 9
    • 0027640858 scopus 로고
    • Learning in the presence of malicious errors
    • M. Kearns and M. Li, Learning in the presence of malicious errors, SIAM Journal on Computing, 22(4): 807-837, 1993.
    • (1993) SIAM Journal on Computing , vol.22 , Issue.4 , pp. 807-837
    • Kearns, M.1    Li, M.2
  • 11
    • 0001663135 scopus 로고
    • Learning Boolean Functions via the Fourier Transform
    • V. P. Roychodhury, K-Y. Siu and A. Orlitsky, ed)
    • Y. Mansour, Learning Boolean Functions via the Fourier Transform. In Theoretical Advances in Neural Computation and Learning, (V. P. Roychodhury, K-Y. Siu and A. Orlitsky, ed), 391-424 (1994).
    • (1994) Theoretical Advances in Neural Computation and Learning , pp. 391-424
    • Mansour, Y.1
  • 12
    • 0021518106 scopus 로고
    • A theory of the learnable
    • L. G. Valiant, A theory of the learnable, Comm. ofthe ACM, 27(11): 1134-1142, 1984.
    • (1984) Comm. Ofthe ACM , vol.27 , Issue.11 , pp. 1134-1142
    • Valiant, L.G.1
  • 13
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    • On the uniform convergence of relative frequencies of events to their probabilities
    • V. Vapnik, A. Chervonenkis, On the uniform convergence of relative frequencies of events to their probabilities. Theory ofPr obability and its Applications, 16(2): 264-280, 1971
    • (1971) Theory Ofpr Obability and Its Applications , vol.16 , Issue.2 , pp. 264-280
    • Vapnik, V.1    Chervonenkis, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.