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Volumn , Issue , 2003, Pages 196-205

Boosting in the presence of noise

Author keywords

Boosting; Machine Learning

Indexed keywords

COMPUTATIONAL COMPLEXITY; LEARNING ALGORITHMS; LEARNING SYSTEMS; SPURIOUS SIGNAL NOISE;

EID: 0038784672     PISSN: 07349025     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (34)

References (16)
  • 1
    • 0032047249 scopus 로고    scopus 로고
    • Specification and simulation of statistical query algorithms for efficiency and noise tolerance
    • J. Aslam and S. Decatur. Specification and simulation of statistical query algorithms for efficiency and noise tolerance. Journal of Computer and System Sciences, 56:191-208, 1998.
    • (1998) Journal of Computer and System Sciences , vol.56 , pp. 191-208
    • Aslam, J.1    Decatur, S.2
  • 2
    • 0001926474 scopus 로고    scopus 로고
    • A polynomial time algorithm for learning noisy linear threshold functions
    • A. Blum, A. Frieze, R. Kannan, and S. Vempala. A polynomial time algorithm for learning noisy linear threshold functions. Algorithmica, 22(1/2):35-52, 1997.
    • (1997) Algorithmica , vol.22 , Issue.1-2 , pp. 35-52
    • Blum, A.1    Frieze, A.2    Kannan, R.3    Vempala, S.4
  • 3
    • 0034250160 scopus 로고    scopus 로고
    • An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
    • T.G. Dietterich. An experimental comparison of three methods for constructing ensembles of decision trees: bagging, boosting, and randomization. Machine Learning, 40(2):139-158, 2000.
    • (2000) Machine Learning , vol.40 , Issue.2 , pp. 139-158
    • Dietterich, T.G.1
  • 4
    • 0034164230 scopus 로고    scopus 로고
    • Additive logistic regression: A statistical view of boosting
    • J. Friedman, T. Hastie, and R. Tibshirani. Additive logistic regression: A statistical view of boosting. The Annals of Statistics, 28:337-374, 2000.
    • (2000) The Annals of Statistics , vol.28 , pp. 337-374
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 5
    • 58149321460 scopus 로고
    • Boosting a weak learning alogrithm by majority
    • Y. Freund. Boosting a weak learning alogrithm by majority. Information and Computation, 121(2),256-285, 1995.
    • (1995) Information and Computation , vol.121 , Issue.2 , pp. 256-285
    • Freund, Y.1
  • 6
    • 0031211090 scopus 로고    scopus 로고
    • A decision-theoretic generalization of on-line learning and an application to boosting
    • Y. Freund and R. Schapire. A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences, 55(1):119-139, 1997.
    • (1997) Journal of Computer and System Sciences , vol.55 , Issue.1 , pp. 119-139
    • Freund, Y.1    Schapire, R.2
  • 8
    • 0345253860 scopus 로고    scopus 로고
    • A pseudorandom generator from any one-way function
    • J. Hastad, R. Impagliazzo, L. Levin, and M. Luby. A pseudorandom generator from any one-way function. SIAM J. Comput., 28(4):1364-1396, 1999.
    • (1999) SIAM J. Comput. , vol.28 , Issue.4 , pp. 1364-1396
    • Hastad, J.1    Impagliazzo, R.2    Levin, L.3    Luby, M.4
  • 10
    • 0032202014 scopus 로고    scopus 로고
    • Efficient noise-tolerant learning from statistical queries
    • M. Kearns. Efficient noise-tolerant learning from statistical queries. Journal of the ACM, 45(6):983-1006, 1998.
    • (1998) Journal of the ACM , vol.45 , Issue.6 , pp. 983-1006
    • Kearns, M.1
  • 11
    • 0033075132 scopus 로고    scopus 로고
    • On the boosting ability of top-down decision tree learning algorithms
    • M. Kearns and Y. Mansour. On the boosting ability of top-down decision tree learning algorithms. Journal of Computer and System Sciences, 58(1):109-128, 1999.
    • (1999) Journal of Computer and System Sciences , vol.58 , Issue.1 , pp. 109-128
    • Kearns, M.1    Mansour, Y.2
  • 12
    • 0028324717 scopus 로고
    • Cryptographic limitations on learning boolean formulae and finite automata
    • M. Kearns and L. Valiant. Cryptographic limitations on learning boolean formulae and finite automata. Journal of the ACM, 41(1):67-95, 1994.
    • (1994) Journal of the ACM , vol.41 , Issue.1 , pp. 67-95
    • Kearns, M.1    Valiant, L.2
  • 15
    • 0025448521 scopus 로고
    • The strength of weak learnability
    • R. Schapire. The strength of weak learnability. Machine Learning, 5(2): 197-227, 1990.
    • (1990) Machine Learning , vol.5 , Issue.2 , pp. 197-227
    • Schapire, R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.