A Multiobjective Sparse Feature Learning Model for Deep Neural Networks.

IEEE Transactions on Neural Networks and Learning Systems(2015)

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摘要
Hierarchical deep neural networks are currently popular learning models for imitating the hierarchical architecture of human brain. Single-layer feature extractors are the bricks to build deep networks. Sparse feature learning models are popular models that can learn useful representations. But most of those models need a user-defined constant to control the sparsity of representations. In this pa...
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关键词
Feature extraction,Pareto optimization,Brain modeling,Neural networks,Linear programming,Evolutionary computation
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