메뉴 건너뛰기




Volumn , Issue , 2007, Pages

Overview of some incremental learning algorithms

Author keywords

[No Author keywords available]

Indexed keywords

EDUCATION; ELECTRIC LOAD MANAGEMENT; FUZZY LOGIC; FUZZY SYSTEMS; LEARNING SYSTEMS; NEURAL NETWORKS;

EID: 50249121225     PISSN: 10987584     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZY.2007.4295640     Document Type: Conference Paper
Times cited : (54)

References (15)
  • 2
    • 50249138553 scopus 로고    scopus 로고
    • A. Bouchachia. Encyclopedia of Data Warehousing and Mining, chapter Incremental Learning. Idea-group, second edition, expected to appear in 2007.
    • A. Bouchachia. Encyclopedia of Data Warehousing and Mining, chapter Incremental Learning. Idea-group, second edition, expected to appear in 2007.
  • 3
    • 0026408256 scopus 로고
    • Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system
    • G. Carpenter, S. Grossberg, and D. Rosen. Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system. Neural Networks, 4(6):759-771, 1991.
    • (1991) Neural Networks , vol.4 , Issue.6 , pp. 759-771
    • Carpenter, G.1    Grossberg, S.2    Rosen, D.3
  • 4
    • 0032923221 scopus 로고    scopus 로고
    • Catastrophic forgetting in connectionist networks: Causes, consequences and solutions
    • R. French. Catastrophic forgetting in connectionist networks: Causes, consequences and solutions. Trends in Cognitive Sciences, Trends in Cognitive Sciences, 3(4):128-135, 1999.
    • (1999) Trends in Cognitive Sciences, Trends in Cognitive Sciences , vol.3 , Issue.4 , pp. 128-135
    • French, R.1
  • 6
    • 0034187078 scopus 로고    scopus 로고
    • General fuzzy min-max neural network for clustering and classification
    • B. Gabrys and A. Bargiela. General fuzzy min-max neural network for clustering and classification. IEEE Transactions on Neural Networks, 11(3):769-783, 2000.
    • (2000) IEEE Transactions on Neural Networks , vol.11 , Issue.3 , pp. 769-783
    • Gabrys, B.1    Bargiela, A.2
  • 7
    • 40649128119 scopus 로고
    • Nonlinear neural networks: Principles, mechanism, and architectures
    • S. Grossberg. Nonlinear neural networks: principles, mechanism, and architectures. Neural Networks, 1:1761, 1988.
    • (1988) Neural Networks , vol.1 , pp. 1761
    • Grossberg, S.1
  • 8
    • 0027632248 scopus 로고
    • Neural gas network for vector quantization and its application to time-series prediction
    • T. Martinetz, S. Berkovich, and K. Schulten. Neural gas network for vector quantization and its application to time-series prediction. IEEE Trans. Neural Networks, 4(4):558569, 1993.
    • (1993) IEEE Trans. Neural Networks , vol.4 , Issue.4 , pp. 558569
    • Martinetz, T.1    Berkovich, S.2    Schulten, K.3
  • 9
    • 77957064197 scopus 로고    scopus 로고
    • Catastrophic interference in connectionist networks: The sequential learning problem
    • M. McCloskey and N. Cohen. Catastrophic interference in connectionist networks: the sequential learning problem. The psychology of learning and motivation, 24:109-164, 1999.
    • (1999) The psychology of learning and motivation , vol.24 , pp. 109-164
    • McCloskey, M.1    Cohen, N.2
  • 10
    • 0031420798 scopus 로고    scopus 로고
    • The neural basis of cognitive development: A constructivist manifesto
    • S. Quartz and T. Sejnowski. The neural basis of cognitive development: a constructivist manifesto. Behavioral and Brain Sciences, 20(4):537-556, 1997.
    • (1997) Behavioral and Brain Sciences , vol.20 , Issue.4 , pp. 537-556
    • Quartz, S.1    Sejnowski, T.2
  • 11
    • 0025407225 scopus 로고
    • Connectionist models of recognition memory: Constraints imposed by learning and forgetting functions
    • R. Ratcliff. Connectionist models of recognition memory: constraints imposed by learning and forgetting functions. Psychological Review, 97:285-308, 1990.
    • (1990) Psychological Review , vol.97 , pp. 285-308
    • Ratcliff, R.1
  • 12
    • 0026156490 scopus 로고
    • A nearest hyperrectangle learning method
    • S. Salzberg. A nearest hyperrectangle learning method. Machine learning, 6:277-309, 1991.
    • (1991) Machine learning , vol.6 , pp. 277-309
    • Salzberg, S.1
  • 13
    • 84945763945 scopus 로고
    • Catastrophic forgetting in connectionist networks: Causes, consequences and solutions
    • N. Sharkey and A. Sharkey. Catastrophic forgetting in connectionist networks: Causes, consequences and solutions. An analysis of catastrophic interference, 7(3-4):301-329, 1995.
    • (1995) An analysis of catastrophic interference , vol.7 , Issue.3-4 , pp. 301-329
    • Sharkey, N.1    Sharkey, A.2
  • 14
    • 0010621345 scopus 로고    scopus 로고
    • J. Sirosh, R. Miikkulainen, and Y. Choe, editors, The UTCS Neural Networks Research Group, Austin, TX, Electronic book
    • J. Sirosh, R. Miikkulainen, and Y. Choe, editors. Lateral Interactions in the Cortex: Structure and Function, The UTCS Neural Networks Research Group, Austin, TX., 1996, Electronic book.
    • (1996) Lateral Interactions in the Cortex: Structure and Function
  • 15
    • 0002564447 scopus 로고
    • An experimental comparison of the nearest-neighbor and nearest-hyperrectangle algorithms
    • D. Wettschereck and T. Dietterich. An experimental comparison of the nearest-neighbor and nearest-hyperrectangle algorithms. Machine Learning, 19(1):5-27, 1995.
    • (1995) Machine Learning , vol.19 , Issue.1 , pp. 5-27
    • Wettschereck, D.1    Dietterich, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.