%0 Journal Article %1 neyshabur2017pacbayesian %A Neyshabur, Behnam %A Bhojanapalli, Srinadh %A Srebro, Nathan %D 2017 %K generalization iclr2018 learning readings spectral %T A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks %U http://arxiv.org/abs/1707.09564 %X 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.

@article{neyshabur2017pacbayesian, 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.}, added-at = {2020-03-03T03:45:15.000+0100}, author = {Neyshabur, Behnam and Bhojanapalli, Srinadh and Srebro, Nathan}, biburl = {https://www.bibsonomy.org/bibtex/2ecfe75307d53056a627ef6f265319560/kirk86}, description = {[1707.09564] A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks}, interhash = {a744faa7b1b1753c2ef1264297dc320e}, intrahash = {ecfe75307d53056a627ef6f265319560}, keywords = {generalization iclr2018 learning readings spectral}, note = {cite arxiv:1707.09564Comment: Accepted to ICLR 2018}, timestamp = {2020-03-03T03:45:15.000+0100}, title = {A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks}, url = {http://arxiv.org/abs/1707.09564}, year = 2017 }