PAC-Bayesian Margin Bounds for Convolutional Neural Networks
Konstantinos Pitas, Mike Davies, Pierre Vandergheynst · arXiv (Cornell University) · 2017
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.