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Volumn , Issue , 2009, Pages 89-96

Active learning for directed exploration of complex systems

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE LEARNING; COMPLEX SYSTEMS; CURRENT SIMULATION; INFORMATION-THEORETIC APPROACH; INPUT PARAMETER; MODEL COMPLEXES; PHYSICS-BASED SIMULATION; PREDICTIVE MODELS; SCIENCE AND ENGINEERING; SYSTEM BEHAVIORS;

EID: 71149121482     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (8)

References (20)
  • 4
    • 0028424239 scopus 로고
    • Improving generalization with active learning
    • Cohn, D., Atlas, L., & Ladner, R. (1994). Improving generalization with active learning. Machine Learning, 15, 201-221.
    • (1994) Machine Learning , vol.15 , pp. 201-221
    • Cohn, D.1    Atlas, L.2    Ladner, R.3
  • 11
    • 1242352526 scopus 로고    scopus 로고
    • Selective sampling for nearest neighbor classifiers
    • Lindenbaum, M., Markovitch, S., & Rusakov, D. (2004). Selective sampling for nearest neighbor classifiers. Machine Learning, 54, 125-152.
    • (2004) Machine Learning , vol.54 , pp. 125-152
    • Lindenbaum, M.1    Markovitch, S.2    Rusakov, D.3
  • 12
    • 0000695404 scopus 로고
    • Information-Based Objective Functions for Active Data Selection
    • MacKay, D. (1992). Information-Based Objective Functions for Active Data Selection. Neural Computation, 4, 590-604.
    • (1992) Neural Computation , vol.4 , pp. 590-604
    • MacKay, D.1
  • 14
    • 33750297394 scopus 로고    scopus 로고
    • Bayesian active learning for sensitivity analysis
    • Pfingsten, T. (2006). Bayesian active learning for sensitivity analysis. Lec. Notes in CS., 4212, 353-364.
    • (2006) Lec. Notes in CS , vol.4212 , pp. 353-364
    • Pfingsten, T.1
  • 15
    • 0003243224 scopus 로고    scopus 로고
    • Probabilistic outputs for support vector machines and comparison to regularized likelihood methods
    • MIT Press
    • Platt, J. (1999). Probabilistic outputs for support vector machines and comparison to regularized likelihood methods. Adv. in Large Margin Classifiers (pp. 61-74). MIT Press.
    • (1999) Adv. in Large Margin Classifiers , pp. 61-74
    • Platt, J.1
  • 17
    • 0042868698 scopus 로고    scopus 로고
    • Support vector machine active learning with applications to text classification
    • Tong, S., & Koller, D. (2001). Support vector machine active learning with applications to text classification. Machine Learning Research, 2, 45-66.
    • (2001) Machine Learning Research , vol.2 , pp. 45-66
    • Tong, S.1    Koller, D.2
  • 20
    • 14344263218 scopus 로고    scopus 로고
    • Learning and evaluating classifiers under sample selection bias
    • Zadrozny, B. (2004). Learning and evaluating classifiers under sample selection bias. Int. Conf. on Machine Learning (p. 114).
    • (2004) Int. Conf. on Machine Learning , pp. 114
    • Zadrozny, B.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.