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Jul, 2016
深度神经网络的分组稀疏正则化
Group Sparse Regularization for Deep Neural Networks
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Simone Scardapane, Danilo Comminiello, Amir Hussain, Aurelio Uncini
TL;DR
探讨了深度神经网络、特征选择和优化之间的关系,并通过引入Group Lasso penalty的方法,同时解决了三个问题,证明此方法可以在大规模分类任务上有效地实现。
Abstract
In this paper, we consider the joint task of simultaneously optimizing (i) the weights of a
deep neural network
, (ii) the number of neurons for each hidden layer, and (iii) the subset of active input features (i.e.,
fea
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