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Volumn 6, Issue , 2017, Pages 4098-4107

The statistical recurrent unit

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS; LONG SHORT-TERM MEMORY; SULFUR DETERMINATION;

EID: 85041927817     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (15)

References (31)
  • 1
    • 85048539791 scopus 로고    scopus 로고
    • NCEP North American Regional Reanalysis. Accesscd:, 10-17
    • NCEP North American Regional Reanalysis. https://data.noaa.gov/dataset/ncep-north-american-regional-reanalysis-narr-for-1979-to-present. Accesscd: 2016-10-17.
    • (2016)
  • 2
    • 85048546521 scopus 로고    scopus 로고
    • Accessed, -10-17
    • Nba movement data. https://github.com/sealneaward/nba-movement-data. Accessed: 2016-10-17.
    • (2016) Nba Movement Data
  • 5
    • 84857855190 scopus 로고    scopus 로고
    • Random search for hyper-parameter optimization
    • Feb
    • Bergstra, James and Bengio, Yoshua. Random search for hyper-parameter optimization. Journal of Machine Learning Research, 13(Feb):281-305, 2012.
    • (2012) Journal of Machine Learning Research , vol.13 , pp. 281-305
    • Bergstra, J.1    Bengio, Y.2
  • 6
    • 84938378229 scopus 로고    scopus 로고
    • Hyperopt: A python library for model selection and hyperparameter optimization
    • Bergstra, James, Komer, Brent, Eliasmith, Chris, Yamins, Dan, and Cox, David D. Hyperopt: A python library for model selection and hyperparameter optimization. Computational Science & Discovery, 8(1):014008, 2015.
    • (2015) Computational Science & Discovery , vol.8 , Issue.1 , pp. 014008
    • Bergstra, J.1    Komer, B.2    Eliasmith, C.3    Yamins, D.4    Cox, D.D.5
  • 12
    • 26444565569 scopus 로고
    • Finding structure in time
    • Elman, Jeffrey L. Finding structure in time. Cognitive science, 14(2): 179-211, 1990.
    • (1990) Cognitive Science , vol.14 , Issue.2 , pp. 179-211
    • Elman, J.L.1
  • 13
    • 84936143793 scopus 로고    scopus 로고
    • Towards end-to-end speech recognition with recurrent neural networks
    • Graves, Alex and Jaitly, Navdeep. Towards end-to-end speech recognition with recurrent neural networks. In ICML, volume 14, pp. 1764-1772, 2014.
    • (2014) ICML , vol.14 , pp. 1764-1772
    • Graves, A.1    Jaitly, N.2
  • 18
    • 34249938474 scopus 로고    scopus 로고
    • Optimization and applications of echo state networks with leaky-integrator neurons
    • Jaeger, Herbert, Luko Sevifiius, Mantas, Popovici, Dan, and Siewert, Udo. Optimization and applications of echo state networks with leaky-integrator neurons. Neural networks, 20(3):335-352, 2007.
    • (2007) Neural Networks , vol.20 , Issue.3 , pp. 335-352
    • Jaeger, H.1    Luko Sevifiius, M.2    Popovici, D.3    Siewert, U.4
  • 27
    • 84892982833 scopus 로고    scopus 로고
    • On the difficulty of training recurrent neural, networks
    • Pascanu, Razvan, Mikolov, Tomas, and Bcngio, Yoshua. On the difficulty of training recurrent neural networks. ICML(3), 28:1310-1318, 2013.
    • (2013) ICML , vol.28 , Issue.3 , pp. 1310-1318
    • Pascanu, R.1    Mikolov, T.2    Bcngio, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.