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Volumn 1, Issue , 2004, Pages 33-37

Recurrent neural networks and pitch representations for music tasks

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION-THROUGH-TIME (BPTT); CHROMATIC CIRCLE (CC); LONG SHORT-TERM MEMORY (LSTM); REAL-TIME RECURRENT LEARNING (RTRL);

EID: 10044278257     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (9)

References (18)
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    • Bakker, B., 2002, Reinforcement Learning with Long Short-Term Memory, Advances in Neural Information Processing Systems, 14, eds. Dietterich, T.G., Becker, S. and Ghahramani, Z., Cambridge, MA: MIT Press.
    • (2002) Advances in Neural Information Processing Systems , vol.14
    • Bakker, B.1
  • 4
    • 84902197186 scopus 로고    scopus 로고
    • Learning the long-term structure of the blues
    • Eck, D. and Schmidhuber, J., 2002, Learning the Long-Term Structure of the Blues. ICANN 2002, 284-289
    • (2002) ICANN 2002 , pp. 284-289
    • Eck, D.1    Schmidhuber, J.2
  • 6
    • 10044280156 scopus 로고    scopus 로고
    • Learning and improvisation
    • eds. Dietterich, T. G., Becker, S., & Ghahramani, Z. Cambridge, MA: MIT Press
    • Franklin, J. A., 2001, Learning and Improvisation, Neural Information Processing Systems 14, eds. Dietterich, T. G., Becker, S., & Ghahramani, Z. Cambridge, MA: MIT Press.
    • (2001) Neural Information Processing Systems , vol.14
    • Franklin, J.A.1
  • 7
    • 0034293152 scopus 로고    scopus 로고
    • Learning to forget: Continual prediction with LSTM
    • Gers, F. A., Schmidhuber, J. and Cummins, F., 2000, Learning to Forget: Continual Prediction with LSTM. Neural Computation 12(10): 2451-2471.
    • (2000) Neural Computation , vol.12 , Issue.10 , pp. 2451-2471
    • Gers, F.A.1    Schmidhuber, J.2    Cummins, F.3
  • 11
    • 0002338623 scopus 로고
    • The representation of pitch in a neural net model of chord classification
    • eds. Todd, P. M. and Loy, E. D. Cambridge, MA: MIT Press
    • Laden, B., and Keefe, D. H., 1991, The Representation of Pitch in a Neural Net Model of Chord Classification. Music and Connectionism, eds. Todd, P. M. and Loy, E. D. Cambridge, MA: MIT Press.
    • (1991) Music and Connectionism
    • Laden, B.1    Keefe, D.H.2
  • 12
    • 21844527162 scopus 로고
    • Neural network music composition by prediction: Exploring the benefits of psychophysical constraints and multiscale processing
    • Mozer, M. C., 1994, Neural Network Music Composition by Prediction: Exploring the Benefits of Psychophysical Constraints and Multiscale Processing. Connection Science, 6, 247-280.
    • (1994) Connection Science , vol.6 , pp. 247-280
    • Mozer, M.C.1
  • 13
    • 0000646059 scopus 로고
    • Learning internal representations by error propagation
    • eds. Rumelhart, D. et al, Cambridge, MA: MIT Press, 1986
    • Rumelhart, D., Hinton, G., and Williams, R., 1986, Learning Internal Representations by Error Propagation, Parallel Distributed Processing 1, eds. Rumelhart, D. et al, Cambridge, MA: MIT Press, pp. 318-362, 1986.
    • (1986) Parallel Distributed Processing , vol.1 , pp. 318-362
    • Rumelhart, D.1    Hinton, G.2    Williams, R.3
  • 15
    • 0002244143 scopus 로고
    • A connectionist approach to algorithmic composition
    • eds. Todd, P.M. and Loy, E. D., Cambridge, MA, MIT Press
    • Todd, P. M., 1991, A Connectionist Approach to Algorithmic Composition, Music and Connectionism, eds. Todd, P.M. and Loy, E. D., Cambridge, MA, MIT Press.
    • (1991) Music and Connectionism
    • Todd, P.M.1
  • 16
    • 0000903748 scopus 로고
    • Generalisation of backpropagation with application to a recurrent gas market model
    • Werbos, P. J., 1988, Generalisation of Backpropagation with Application to a Recurrent Gas Market Model, Neural Networks, 1:339-356.
    • (1988) Neural Networks , vol.1 , pp. 339-356
    • Werbos, P.J.1
  • 17
    • 0001609567 scopus 로고
    • An efficient gradient-based algorithm for on-line training of recurrent network trajectories
    • Williams, R. J., and Peng, J., 1990, An Efficient Gradient-based Algorithm for On-line Training of Recurrent Network Trajectories, Neural Computation, 2(4): 490-501.
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    • Williams, R.J.1    Peng, J.2
  • 18
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    • A learning algorithm for continually running fully recurrent networks
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.