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Volumn 5, Issue , 2017, Pages 3900-3916

Sequence to better sequence: Continuous revision of combinatorial structures

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; GRADIENT METHODS;

EID: 85047006547     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (27)

References (28)
  • 4
    • 55949089312 scopus 로고    scopus 로고
    • A first look at music composition using lstm recurrent neural networks
    • Eck, D. and Schmidhuber, J. A first look at music composition using lstm recurrent neural networks. IDSIA Technical Report, 2002.
    • (2002) IDSIA Technical Report
    • Eck, D.1    Schmidhuber, J.2
  • 9
    • 84947598017 scopus 로고    scopus 로고
    • Squeezing bottlenecks: Exploring the limits of autoencoder semantic representation capabilities
    • Gupta, R, Banchs, R. E., and Rosso, R Squeezing bottlenecks: Exploring the limits of autoencoder semantic representation capabilities. Neurocomputing, 175:1001-1008, 2016.
    • (2016) Neurocomputing , vol.175 , pp. 1001-1008
    • Gupta, R.1    Banchs, R.E.2    Rosso, R.3
  • 13
    • 85030979929 scopus 로고    scopus 로고
    • The unreasonable effectiveness of recurrent neural networks
    • URL karpathy.github.io
    • Karpathy, A. The unreasonable effectiveness of recurrent neural networks. Andrej Karpathy blog, 2015. URL karpathy.github.io.
    • (2015) Andrej Karpathy Blog
    • Karpathy, A.1
  • 20
    • 84946206172 scopus 로고    scopus 로고
    • Deep neural networks are easily fooled: High confidence predictions for unrecognizable images
    • Nguyen, A., Yosinski, J., and Clune, J. Deep neural networks are easily fooled: High confidence predictions for unrecognizable images. Computer Vision and Pattern Recognition, 2015.
    • (2015) Computer Vision and Pattern Recognition
    • Nguyen, A.1    Yosinski, J.2    Clune, J.3
  • 22
    • 85083953896 scopus 로고    scopus 로고
    • Deep inside convolutional networks: Visualising image classification models and saliency maps
    • Simonyan, K., Vedaldi, A., and Zisserman, A. Deep inside convolutional networks: Visualising image classification models and saliency maps. ICLR Workshop Proceedings, 2014.
    • (2014) ICLR Workshop Proceedings
    • Simonyan, K.1    Vedaldi, A.2    Zisserman, A.3
  • 27
    • 0037236821 scopus 로고    scopus 로고
    • An elementary proof of a theorem of Johnson and lindenstrauss
    • Dasgupta, S. D. A. and Gupta, A. K. An elementary proof of a theorem of Johnson and lindenstrauss. Random Structures and Algorithms, 22:60-65, 2002.
    • (2002) Random Structures and Algorithms , vol.22 , pp. 60-65
    • Dasgupta, S.D.A.1    Gupta, A.K.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.