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Volumn , Issue , 2018, Pages 3390-3398

Measuring catastrophic forgetting in neural networks

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIRDS;

EID: 85057759997     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (638)

References (37)
  • 1
    • 13144294059 scopus 로고    scopus 로고
    • Memory retention-the synaptic stability versus plasticity dilemma
    • Abraham, W. C., and Robins, A. 2005. Memory retention-the synaptic stability versus plasticity dilemma. Trends in Neurosciences 28(2):73-78.
    • (2005) Trends in Neurosciences , vol.28 , Issue.2 , pp. 73-78
    • Abraham, W.C.1    Robins, A.2
  • 3
    • 84885190141 scopus 로고    scopus 로고
    • Ensemble learning in fixed expansion layer networks for mitigating catastrophic forgetting
    • Coop, R.; Mishtal, A.; and Arel, I. 2013. Ensemble learning in fixed expansion layer networks for mitigating catastrophic forgetting. IEEE Trans. on Neural Networks and Learning Systems 24(10):1623-1634.
    • (2013) IEEE Trans. on Neural Networks and Learning Systems , vol.24 , Issue.10 , pp. 1623-1634
    • Coop, R.1    Mishtal, A.2    Arel, I.3
  • 4
    • 34547972773 scopus 로고    scopus 로고
    • Boosting for transfer learning
    • ACM
    • Dai, W.; Yang, Q.; Xue, G.-R.; and Yu, Y. 2007. Boosting for transfer learning. In ICML, 193-200. ACM.
    • (2007) ICML , pp. 193-200
    • Dai, W.1    Yang, Q.2    Xue, G.-R.3    Yu, Y.4
  • 6
    • 0000091024 scopus 로고
    • A composite holographic associative recall model
    • Eich, J. M. 1982. A composite holographic associative recall model. Psych. Review 89(6):627.
    • (1982) Psych. Review , vol.89 , Issue.6 , pp. 627
    • Eich, J.M.1
  • 8
    • 0347683832 scopus 로고    scopus 로고
    • Pseudo-recurrent connectionist networks: An approach to the 'sensitivity-stability' dilemma
    • French, R. M. 1997. Pseudo-recurrent connectionist networks: An approach to the 'sensitivity-stability' dilemma. Connection Science 9(4):353-380.
    • (1997) Connection Science , vol.9 , Issue.4 , pp. 353-380
    • French, R.M.1
  • 9
    • 0032923221 scopus 로고    scopus 로고
    • Catastrophic forgetting in connectionist networks
    • French, R. M. 1999. Catastrophic forgetting in connectionist networks. Trends in Cognitive Sciences 3(4):128-135.
    • (1999) Trends in Cognitive Sciences , vol.3 , Issue.4 , pp. 128-135
    • French, R.M.1
  • 11
    • 84960130481 scopus 로고    scopus 로고
    • A bio-inspired incremental learning architecture for applied perceptual problems
    • Gepperth, A., and Karaoguz, C. 2016. A bio-inspired incremental learning architecture for applied perceptual problems. Cognitive Computation 8(5):924-934.
    • (2016) Cognitive Computation , vol.8 , Issue.5 , pp. 924-934
    • Gepperth, A.1    Karaoguz, C.2
  • 13
    • 84908474554 scopus 로고    scopus 로고
    • Unsupervised neuron selection for mitigating catastrophic forgetting in neural networks
    • 2014, IEEE
    • Goodrich, B., and Arel, I. 2014. Unsupervised neuron selection for mitigating catastrophic forgetting in neural networks. In IEEE 57th Int. Midwest Symposium on Circuits and Systems (MWSCAS), 2014, 997-1000. IEEE.
    • (2014) IEEE 57th Int. Midwest Symposium on Circuits and Systems (MWSCAS) , pp. 997-1000
    • Goodrich, B.1    Arel, I.2
  • 14
    • 84986274465 scopus 로고    scopus 로고
    • Deep residual learning for image recognition
    • He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016. Deep residual learning for image recognition. In CVPR, 770-778.
    • (2016) CVPR , pp. 770-778
    • He, K.1    Zhang, X.2    Ren, S.3    Sun, J.4
  • 15
    • 85023741194 scopus 로고    scopus 로고
    • Cnn architectures for large-scale audio classification
    • Hershey, S.; Chaudhuri, S.; Ellis, D. P.; et al. 2017. Cnn architectures for large-scale audio classification. In ICASSP.
    • (2017) ICASSP
    • Hershey, S.1    Chaudhuri, S.2    Ellis, D.P.3
  • 17
    • 85020874517 scopus 로고    scopus 로고
    • Visual question answering: Datasets, algorithms, and future challenges
    • Kafle, K., and Kanan, C. 2017. Visual question answering: Datasets, algorithms, and future challenges. Computer Vision and Image Understanding.
    • (2017) Computer Vision and Image Understanding
    • Kafle, K.1    Kanan, C.2
  • 21
    • 0026477904 scopus 로고
    • Alcove: An exemplar-based connectionist model of category learning
    • Kruschke, J. K. 1992. Alcove: An exemplar-based connectionist model of category learning. Psych. review 99(1):22.
    • (1992) Psych. Review , vol.99 , Issue.1 , pp. 22
    • Kruschke, J.K.1
  • 22
    • 84945230598 scopus 로고    scopus 로고
    • Fully convolutional networks for semantic segmentation
    • Long, J.; Shelhamer, E.; and Darrell, T. 2015. Fully convolutional networks for semantic segmentation. In CVPR, 3431-3440.
    • (2015) CVPR , pp. 3431-3440
    • Long, J.1    Shelhamer, E.2    Darrell, T.3
  • 23
    • 77957064197 scopus 로고
    • Catastrophic interference in connectionist networks: The sequential learning problem
    • McCloskey, M., and Cohen, N. J. 1989. Catastrophic interference in connectionist networks: The sequential learning problem. Psych. of Learning & Motivation 24:109-165.
    • (1989) Psych. of Learning & Motivation , vol.24 , pp. 109-165
    • McCloskey, M.1    Cohen, N.J.2
  • 25
    • 58149368051 scopus 로고
    • A distributed memory model for serial-order information
    • Murdock, B. B. 1983. A distributed memory model for serial-order information. Psych. Review 90(4):316.
    • (1983) Psych. Review , vol.90 , Issue.4 , pp. 316
    • Murdock, B.B.1
  • 28
    • 85017151114 scopus 로고    scopus 로고
    • Life-long learning based on dynamic combination model
    • Ren, B.; Wang, H.; Li, J.; and Gao, H. 2017. Life-long learning based on dynamic combination model. Applied Soft Computing 56:398-404.
    • (2017) Applied Soft Computing , vol.56 , pp. 398-404
    • Ren, B.1    Wang, H.2    Li, J.3    Gao, H.4
  • 29
    • 38149038993 scopus 로고
    • Catastrophic forgetting, rehearsal and pseudorehearsal
    • Robins, A. 1995. Catastrophic forgetting, rehearsal and pseudorehearsal. Connection Science 7(2):123-146.
    • (1995) Connection Science , vol.7 , Issue.2 , pp. 123-146
    • Robins, A.1
  • 31
    • 84946751287 scopus 로고    scopus 로고
    • Facenet: A unified embedding for face recognition and clustering
    • Schroff, F.; Kalenichenko, D.; and Philbin, J. 2015. Facenet: A unified embedding for face recognition and clustering. In CVPR, 815-823.
    • (2015) CVPR , pp. 815-823
    • Schroff, F.1    Kalenichenko, D.2    Philbin, J.3
  • 32
    • 84945763945 scopus 로고
    • An analysis of catastrophic interference
    • Sharkey, N. E., and Sharkey, A. J. 1995. An analysis of catastrophic interference. Connection Science 7:301-329.
    • (1995) Connection Science , vol.7 , pp. 301-329
    • Sharkey, N.E.1    Sharkey, A.J.2
  • 37
    • 1942451938 scopus 로고    scopus 로고
    • Feature selection for high-dimensional data: A fast correlation-based filter solution
    • Yu, L., and Liu, H. 2003. Feature selection for high-dimensional data: A fast correlation-based filter solution. In ICML, 856-863.
    • (2003) ICML , pp. 856-863
    • Yu, L.1    Liu, H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.