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Our proposed deeply-supervised nets (DSN) method simultaneously minimizes classification error while making the learning process of hidden layers direct and transparent.
Distributed representations, simple recurrent networks, and grammatical
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Understanding the difficulty of training deep feedforward neural networks
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Q. Le, J. Ngiam, Z. Chen, D. Chia, P. W. Koh, and A. Ng · 2010
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Regularization of neural networks using dropconnect
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Regularized m-estimators with nonconvexity : statistical and algorithmic theory for local optima
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Visualizing and understanding convolutional networks
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Stochastic pooling for regularization of deep convolutional neural networks
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