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An adversary is essentially an algorithm intent on making a classification system perform in some particular way given an input, e.g., increase the probability of a false negative.
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Automatic musical pattern feature extraction using convolutional neural network
T. LH. Li, A. B. Chan, and A. HW. Chun · 2010
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The million song dataset
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Unsupervised learning of sparse features for scalable audio classification
M. Henaff, K. Jarrett, K. Kavukcuoglu, and Y. LeCun · 2011
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Deep belief networks for automatic music genre classification
X. Yang, Q. Chen, S. Zhou, and X. Wang · 2011
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Music Emotion Recognition
Y.-H. Yang and H. H. Chen · 2011
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Deep neural networks are easily fooled: High confidence predictions for unrecognizable images
A. Nguyen, J. Yosinski, and J. Clune · 2014
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Improved music feature learning with deep neural networks
S. Sigtia and S. Dixon · 2014
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A simple method to determine if a music information retrieval system is a “horse”
B. L. Sturm · 2014
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The state of the art ten years after a state of the art: Future research in music information retrieval
B. L. Sturm · 2014
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A survey of evaluation in music genre recognition
B. L. Sturm · 2014
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A closer look at deep learning neural networks with low-level spectral periodicity features
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On-line continuous-time music mood regression with deep recurrent neural networks
F. Weninger, F. Eyben, and B. Schuller · 2014
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A deep representation for invariance and music classification
Chiyuan Zhang, G. Evangelopoulos, S. Voinea, L. Rosasco, and T. Poggio · 2014
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Deep Learning
Y. Bengio, I. Goodfellow, and A. Courville · 2015
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Explaining and harnessing adversarial examples
I. J. Goodfellow, J. Shlens, and C. Szegedy · 2015
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Deep learning, audio adversaries, and music content analysis
C. Kereliuk, B. L. Sturm, and J. Larsen · 2015
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“horse” inside: Seeking causes of the behaviours of music content analysis systems
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¿ el caballo viejo? latin genre recognition with deep learning and spectral periodicity
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