论文标题
使用神经网络的分类问题的先验估计
A priori estimates for classification problems using neural networks
论文作者
论文摘要
我们考虑使用神经网络的假设类别考虑二进制和多类分类问题。对于给定的假设类别，我们使用Rademacher复杂性估计值和直接近似定理来获得正则损耗功能的先验误差估计。
We consider binary and multi-class classification problems using hypothesis classes of neural networks. For a given hypothesis class, we use Rademacher complexity estimates and direct approximation theorems to obtain a priori error estimates for regularized loss functionals.
