Structure Learning for Deep Neural Networks Based on Multiobjective Optimization.

IEEE Transactions on Neural Networks and Learning Systems(2018)

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摘要
This paper focuses on the connecting structure of deep neural networks and proposes a layerwise structure learning method based on multiobjective optimization. A model with better generalization can be obtained by reducing the connecting parameters in deep networks. The aim is to find the optimal structure with high representation ability and better generalization for each layer. Then, the visible...
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关键词
Joining processes,Biological neural networks,Computational modeling,Pareto optimization,Computer architecture
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