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PAC-Bayesian Margin Bounds for Convolutional Neural Networks
Published 30 Dec 2017 in cs.LG and stat.ML | (1801.00171v2)
Abstract: 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.
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