%0 Generic %1 e2019generalization %A E, Weinan %A Ma, Chao %A Wu, Lei %D 2019 %K 2019 machine-learning %T On the Generalization Properties of Minimum-norm Solutions for Over-parameterized Neural Network Models %U http://arxiv.org/abs/1912.06987 %X We study the generalization properties of minimum-norm solutions for three over-parametrized machine learning models including the random feature model, the two-layer neural network model and the residual network model. We proved that for all three models, the generalization error for the minimum-norm solution is comparable to the Monte Carlo rate, up to some logarithmic terms, as long as the models are sufficiently over-parametrized.

@misc{e2019generalization, abstract = {We study the generalization properties of minimum-norm solutions for three over-parametrized machine learning models including the random feature model, the two-layer neural network model and the residual network model. We proved that for all three models, the generalization error for the minimum-norm solution is comparable to the Monte Carlo rate, up to some logarithmic terms, as long as the models are sufficiently over-parametrized.}, added-at = {2019-12-18T09:28:20.000+0100}, author = {E, Weinan and Ma, Chao and Wu, Lei}, biburl = {https://www.bibsonomy.org/bibtex/2aafa949e43a5ee3e6a9d145dddc76643/analyst}, description = {[1912.06987] On the Generalization Properties of Minimum-norm Solutions for Over-parameterized Neural Network Models}, interhash = {41c030fd20a981721d442b5f45f1573a}, intrahash = {aafa949e43a5ee3e6a9d145dddc76643}, keywords = {2019 machine-learning}, note = {cite arxiv:1912.06987}, timestamp = {2019-12-18T09:28:20.000+0100}, title = {On the Generalization Properties of Minimum-norm Solutions for Over-parameterized Neural Network Models}, url = {http://arxiv.org/abs/1912.06987}, year = 2019 }