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Volumn 1, Issue , 2006, Pages 362-367

Active learning with near misses

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; FUNCTIONS; PROBLEM SOLVING; VISUAL COMMUNICATION;

EID: 33750698602     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (14)

References (19)
  • 1
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    • Baum, E.B.1
  • 2
    • 0028424239 scopus 로고
    • Improving generalization with active learning
    • Cohn, D.; Atlas, L.; and Ladner, R. 1994. Improving generalization with active learning. Machine Learning 15(2):201-221.
    • (1994) Machine Learning , vol.15 , Issue.2 , pp. 201-221
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  • 4
    • 0025721732 scopus 로고
    • Query-based learning applied to partially trained multilayer perceptrons
    • Hwang, J.-N.; Choi, J.; Oh, S.; and Marks, R.J., I. 1991. Query-based learning applied to partially trained multilayer perceptrons. IEEE Transactions on Neural Networks 2(1):131-136.
    • (1991) IEEE Transactions on Neural Networks , vol.2 , Issue.1 , pp. 131-136
    • Hwang, J.-N.1    Choi, J.2    Oh, S.3    Marks, R.J.I.4
  • 5
    • 33750595414 scopus 로고
    • Query learning can work poorly when a human oracle is used
    • Lang, K. J., and Baum, E. B. 1992. Query learning can work poorly when a human oracle is used. In UCNN'92.
    • (1992) UCNN'92
    • Lang, K.J.1    Baum, E.B.2
  • 6
    • 1242352526 scopus 로고    scopus 로고
    • Selective sampling for nearest neighbor classifiers
    • Lindenbaum, M.; Markovitch, S.; and Rusakov, D. 2004. Selective sampling for nearest neighbor classifiers. Machine Learning 54(2):125-152.
    • (2004) Machine Learning , vol.54 , Issue.2 , pp. 125-152
    • Lindenbaum, M.1    Markovitch, S.2    Rusakov, D.3
  • 8
    • 1242310003 scopus 로고    scopus 로고
    • Incremental learning with partial instance memory
    • Maloof, M. A., and Michalski, R. S. 2004. Incremental learning with partial instance memory. Artificial Intelligence 154:95-126.
    • (2004) Artificial Intelligence , vol.154 , pp. 95-126
    • Maloof, M.A.1    Michalski, R.S.2
  • 9
    • 14344251601 scopus 로고    scopus 로고
    • Diverse ensembles for active learning
    • Melville, P., and Mooney, R. 2004. Diverse ensembles for active learning. In ICML'04, 584-591.
    • (2004) ICML'04 , pp. 584-591
    • Melville, P.1    Mooney, R.2
  • 10
    • 33750685483 scopus 로고    scopus 로고
    • Function-based classification from 3D data via generic and symbolic models
    • Pechuk, M.; Soldea, O.; and Rivlin, E. 2005. Function-based classification from 3D data via generic and symbolic models. In AAAI'05.
    • (2005) AAAI'05
    • Pechuk, M.1    Soldea, O.2    Rivlin, E.3
  • 11
    • 0003212629 scopus 로고
    • Efficient training of artificial neural networks for autonomous navigation
    • Pomerleau, D. 1991. Efficient training of artificial neural networks for autonomous navigation. Neural Computation 3(1):88-97.
    • (1991) Neural Computation , vol.3 , Issue.1 , pp. 88-97
    • Pomerleau, D.1
  • 12
    • 0001325621 scopus 로고
    • Experimental goal regression: A method for learning problem-solving heuristics
    • Porter, B. W., and Kibler, D. F. 1986. Experimental goal regression: A method for learning problem-solving heuristics. Machine Learning 1(3):249-285.
    • (1986) Machine Learning , vol.1 , Issue.3 , pp. 249-285
    • Porter, B.W.1    Kibler, D.F.2
  • 13
    • 0000606355 scopus 로고
    • Empirical learning as a function of concept character
    • Rendell, L., and Cho, H. 1990. Empirical learning as a function of concept character. Machine Learning 5(3):267-298.
    • (1990) Machine Learning , vol.5 , Issue.3 , pp. 267-298
    • Rendell, L.1    Cho, H.2
  • 15
    • 84902142380 scopus 로고    scopus 로고
    • Incorporating invariances in support vector learning machines
    • Scholkopf, B.; Burges, C.; and Vapnik, V. 1996. Incorporating invariances in support vector learning machines. In ICANN'96, 47-52.
    • (1996) ICANN'96 , pp. 47-52
    • Scholkopf, B.1    Burges, C.2    Vapnik, V.3
  • 16
    • 0026244101 scopus 로고
    • Achieving generalized object recognition through reasoning about association of function to structure
    • Stark, L., and Bowyer, K. W. 1991. Achieving generalized object recognition through reasoning about association of function to structure. IEEE Transactions on Pattern Analysis and Machine Intelligence 13(10):1097-1104.
    • (1991) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.13 , Issue.10 , pp. 1097-1104
    • Stark, L.1    Bowyer, K.W.2
  • 17
    • 0020894549 scopus 로고
    • Learning physical descriptions from functional definitions, examples, and precedents
    • Winston, P. H.; Binford, T.; Katz, B.; and Lowry, M. 1983. Learning physical descriptions from functional definitions, examples, and precedents. In AAAI'03, 433-439.
    • (1983) AAAI'03 , pp. 433-439
    • Winston, P.H.1    Binford, T.2    Katz, B.3    Lowry, M.4
  • 18
    • 0000027741 scopus 로고
    • New York, NY: McGraw-Hill. chapter Learning Structural Descriptions From Examples
    • Winston, P. H. 1975. The Psychology of Computer Vision. New York, NY: McGraw-Hill. chapter Learning Structural Descriptions From Examples, 157-209.
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    • Winston, P.H.1
  • 19
    • 0031349264 scopus 로고    scopus 로고
    • Sparse representations for fast, one-shot learning
    • Yip, K., and Sussman, G. J. 1997. Sparse representations for fast, one-shot learning. In AAAI'97, 521-527.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.