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The computer vision literature shows that randomly weighted neural networks perform reasonably as feature extractors.
Calculation of a constant q spectral transform
Judith C Brown · 1991
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Feedforward neural networks with random weights
Wouter F Schmidt, Martin A Kraaijveld, and Robert PW Duin · 1992
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Learning and generalization characteristics of the random vector functional-link net
Yoh-Han Pao, Gwang-Hoon Park, and Dejan J Sobajic · 1994
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The “echo state” approach to analysing and training recurrent neural networks-with an erratum note
Herbert Jaeger · 2001
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Musical genre classification of audio signals
George Tzanetakis and Perry Cook · 2002
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ISMIR 2004 audio description contest
Pedro Cano, Emilia Gómez, Fabien Gouyon, Perfecto Herrera, Markus Koppenberger, Beesuan Ong, Xavier Serra, Sebastian Streich, and Nicolas Wack · 2006
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Extreme learning machine: theory and applications
Guang-Bin Huang, Qin-Yu Zhu, and Chee-Kheong Siew · 2006
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Elm for the classification of music genres
Qi-Jun Benedict Loh and Sabu Emmanuel · 2006
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Reservoir computing: A powerful black-box framework for nonlinear audio processing
Georg Holzmann · 2009
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Unsupervised feature learning for audio classification using convolutional deep belief networks
Honglak Lee, Peter Pham, Yan Largman, and Andrew Y Ng · 2009
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Deep sparse rectifier neural networks
Xavier Glorot, Antoine Bordes, and Yoshua Bengio · 2011
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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
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On random weights and unsupervised feature learning
Andrew M Saxe, Pang Wei Koh, Zhenghao Chen, Maneesh Bhand, Bipin Suresh, and Andrew Y Ng · 2011
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Automatic han chinese folk song classification using extreme learning machines
Suisin Khoo, Zhihong Man, and Zhenwei Cao · 2012
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Music classification using extreme learning machines
Simone Scardapane, Danilo Comminiello, Michele Scarpiniti, and Aurelio Uncini · 2013
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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End-to-end learning for music audio
Sander Dieleman and Benjamin Schrauwen · 2014
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
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Speech emotion recognition using deep neural network and extreme learning machine
Kun Han, Dong Yu, and Ivan Tashev · 2014
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A dataset and taxonomy for urban sound research
J. Salamon, C. Jacoby, and J. P. Bello · 2014
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Improved musical onset detection with convolutional neural networks
Jan Schluter and Sebastian Bock · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Transfer learning for music classification and regression tasks
Keunwoo Choi, György Fazekas, Mark Sandler, and Kyunghyun Cho · 2017
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Audio to score matching by combining phonetic and duration information
Rong Gong, Jordi Pons, and Xavier Serra · 2017
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Densely connected convolutional networks
Gao Huang, Zhuang Liu, Kilian Q Weinberger, and Laurens van der Maaten · 2017
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Dlr: Toward a deep learned rhythmic representation for music content analysis
Yeonwoo Jeong, Keunwoo Choi, and Hosan Jeong · 2017
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Sample-level deep convolutional neural networks for music auto-tagging using raw waveforms
Jongpil Lee, Jiyoung Park, Keunhyoung Luke Kim, and Juhan Nam · 2017
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Djork-Arné Clevert, Thomas Unterthiner, and Sepp Hochreiter · 2015
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Deep learning and music adversaries
Corey Kereliuk, Bob L Sturm, and Jan Larsen · 2015
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Automatic tagging using deep convolutional neural networks
Keunwoo Choi, George Fazekas, and Mark Sandler · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Combining modality-specific extreme learning machines for emotion recognition in the wild
Heysem Kaya and Albert Ali Salah · 2016
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Scale and shift invariant time/frequency representation using auditory statistics: Application to rhythm description
Ugo Marchand and Geoffroy Peeters · 2016
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Sergio Oramas, Oriol Nieto, Francesco Barbieri, and Xavier Serra · 2017
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Score-informed syllable segmentation for a cappella singing voice with convolutional neural networks
Jordi Pons, Rong Gong, and Xavier Serra · 2017
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End-to-end learning for music audio tagging at scale
Jordi Pons, Oriol Nieto, Matthew Prockup, Erik M Schmidt, Andreas F Ehmann, and Xavier Serra · 2017
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Designing efficient architectures for modeling temporal features with convolutional neural networks
Jordi Pons and Xavier Serra · 2017
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Timbre analysis of music audio signals with convolutional neural networks
Jordi Pons, Olga Slizovskaia, Rong Gong, Emilia Gómez, and Xavier Serra · 2017
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Semi-supervised echo state networks for audio classification
Simone Scardapane and Aurelio Uncini · 2017
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Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky · 2017
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Local explanation methods for deep neural networks lack sensitivity to parameter values
Julius Adebayo, Justin Gilmer, Ian Goodfellow, and Been Kim · 2018
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Jaehun Kim, Julián Urbano, Cynthia Liem, and Alan Hanjalic · 2018
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Samplecnn: End-to-end deep convolutional neural networks using very small filters for music classification
Jongpil Lee, Jiyoung Park, Keunhyoung Luke Kim, and Juhan Nam · 2018
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A Wavenet for speech denoising
Dario Rethage, Jordi Pons, and Xavier Serra · 2018
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Intriguing properties of randomly weighted networks: Generalizing while learning next to nothing
Amir Rosenfeld and John K Tsotsos · 2018
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