title: A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks
abstract: We present a generalization bound for feedforward neural networks in terms of the product of the spectral norm of the layers and the Frobenius norm of the weights.  The generalization bound is derived using a PAC-Bayes analysis.
authors: Behnam Neyshabur Srinadh Bhojanapalli Nathan Srebro
hIndex: Nathan Srebro 63