메뉴 건너뛰기




Volumn , Issue , 2016, Pages 850-855

Dynamic entity representation with max-pooling improves machine reading

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; NEURAL NETWORKS;

EID: 84994145773     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.18653/v1/n16-1099     Document Type: Conference Paper
Times cited : (43)

References (20)
  • 4
    • 84953873103 scopus 로고    scopus 로고
    • Generating sequences with recurrent neural networks
    • abs/1308.0850
    • Alex Graves. 2013. Generating sequences with recurrent neural networks. CoRR, abs/1308.0850.
    • (2013) CoRR
    • Graves, A.1
  • 6
    • 84994131972 scopus 로고    scopus 로고
    • The goldilocks principle: Reading children's books with explicit memory representations
    • abs/1511.02301
    • Felix Hill, Antoine Bordes, Sumit Chopra, and Jason Weston. 2015. The goldilocks principle: Reading children's books with explicit memory representations. CoRR, abs/1511.02301.
    • (2015) CoRR
    • Hill, F.1    Bordes, A.2    Chopra, S.3    Weston, J.4
  • 10
    • 0032203257 scopus 로고    scopus 로고
    • Gradient-based learning applied to document recognition
    • Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner. 1998. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11):2278-2324.
    • (1998) Proceedings of the IEEE , vol.86 , Issue.11 , pp. 2278-2324
    • LeCun, Y.1    Bottou, L.2    Bengio, Y.3    Haffner, P.4
  • 17
    • 0000997226 scopus 로고
    • "Cloze procedure": A new tool for measuring readability
    • Wilson L. Taylor. 1953. "cloze procedure": a new tool for measuring readability. Journalism Quarterly, 30:415-433.
    • (1953) Journalism Quarterly , vol.30 , pp. 415-433
    • Taylor, W.L.1
  • 18
    • 84893343292 scopus 로고    scopus 로고
    • Lecture 6.5 - msprop: Divide the gradient by a running average of its recent magnitude
    • Tijmen Tieleman and Geoffrey Hinton. 2012. Lecture 6.5 - msprop: Divide the gradient by a running average of its recent magnitude. COURSERA: Neural Networks for Machine Learning.
    • (2012) COURSERA: Neural Networks for Machine Learning
    • Tieleman, T.1    Hinton, G.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.