PAC-Bayesian Margin Bounds for Convolutional Neural Networks

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Apr 20, 2018
Konstantinos Pitas, Mike Davies, Pierre Vandergheynst
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Recently the generalization error of deep neural networks has been analyzed through the PAC-Bayesian framework, for the case of fully connected layers. We adapt this approach to the convolutional setting.

* arXiv admin note: text overlap with arXiv:1707.09564 by other authors  
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