A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks

Behnam Neyshabur, Srinadh Bhojanapalli, Nathan Srebro

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.

Knowledge Graph

arrow_drop_up

Comments

Sign up or login to leave a comment