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In the domain of algorithmic music composition, machine learning-driven systems eliminate the need for carefully hand-crafting rules for composition.
Geometrical approximations to the structure of musical pitch
Roger N Shepard · 1982
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A connectionist approach to algorithmic composition
Peter M Todd · 1989
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Learning from delayed rewards
Christopher John Cornish Hellaby Watkins · 1989
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Connectionist music composition based on melodic and stylistic constraints
Michael C Mozer and Todd Soukup · 1991
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Neural network-based method for chord/note scale association with melodies
Naoki Shibata · 1991
Earlier work this paper cites.
Q-learning
Christopher JCH Watkins and Peter Dayan · 1992
Earlier work this paper cites.
Learning long-term dependencies with gradient descent is difficult
Yoshua Bengio, Patrice Simard, and Paolo Frasconi · 1994
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Improving elevator performance using reinforcement learning
Robert H Crites and Andrew G Barto · 1996
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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A connectionist model of tension in chord progressions
AF Melo · 1998
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Learning to forget: Continual prediction with lstm
Felix A. Gers, Jürgen Schmidhuber, and Fred Cummins · 1999
Cited alongside, same era.
Multi-phase learning for jazz improvisation and interaction
Judy A Franklin · 2001
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A first look at music composition using lstm recurrent neural networks
Douglas Eck and Juergen Schmidhuber · 2002
Cited alongside, same era.
Recurrent neural networks and pitch representations for music tasks
Judy A Franklin · 2004
Cited alongside, same era.
Modeling temporal dependencies in high-dimensional sequences: application to polyphonic music generation and transcription
Nicolas Boulanger-Lewandowski, Yoshua Bengio, and Pascal Vincent · 2012
Song from pi: A musically plausible network for pop music generation
Hang Chu, Raquel Urtasun, and Sanja Fidler · 2016
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Algorithmic composition of melodies with deep recurrent neural networks
Florian Colombo, Samuel Pavio Muscinelli, Alex Seeholzer, Johanni Brea, and Wulfram Gerstner · 2016
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Bachbot: Automatic composition in the style of bach chorales
Feynman Liang · 2016
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Composing music with grammar argumented neural networks and note-level encoding
Zheng Sun, Jiaqi Liu, Zewang Zhang, Jingwen Chen, Zhao Huo, Ching Hua Lee, and Xiao Zhang · 2016
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Music generation by deep learning-challenges and directions
Jean-Pierre Briot and Francois Pachet · 2017
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Cited alongside, same era.
Ai methods in algorithmic composition: A comprehensive survey
Jose D Fernández and Francisco Vico · 2013
Cited alongside, same era.
Markov decision processes: discrete stochastic dynamic programming
Martin L Puterman · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
Cited alongside, same era.
Deepbach: a steerable model for bach chorales generation
Gaëtan Hadjeres, François Pachet, and Frank Nielsen · 2017
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Tuning recurrent neural networks with reinforcement learning
Natasha Jaques, Shixiang Gu, Dzmitry Bahdanau, Jose Miguel Hernandez Lobato, Richard E Turner, and Doug Eck · 2017
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Midinet: A convolutional generative adversarial network for symbolic-domain music generation
Li-Chia Yang, Szu-Yu Chou, and Yi-Hsuan Yang · 2017
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