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Designing architectures for deep neural networks requires expert knowledge and substantial computation time.
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How transferable are features in deep neural networks?
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Unsupervised representation learning with deep convolutional generative adversarial networks
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Practical bayesian optimization of machine learning algorithms
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R. K. Srivastava, K. Greff, and J. Schmidhuber · 2015
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Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, and J. Xiao · 2015
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Normalization propagation: A parametric technique for removing internal covariate shift in deep networks
D. Arpit, Y. Zhou, B.U. Kota, and V. Govindaraju · 2016
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Layer normalization
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C. Szegedy, S. Ioffe, and V. Vanhoucke · 2016
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Designing neural network architectures using reinforcement learning
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