论文标题
团体卷积神经网络的VC维度
VC dimensions of group convolutional neural networks
论文作者
论文摘要
我们研究群体卷积神经网络的概括能力。我们确定了小组卷积神经网络简单集合的VC维度的精确估计。特别是，我们发现，对于无限群体和适当选择的卷积内核，尽管卷积神经网络的两参数家族具有无限的VC维度，尽管无限群体的行动不变。
We study the generalization capacity of group convolutional neural networks. We identify precise estimates for the VC dimensions of simple sets of group convolutional neural networks. In particular, we find that for infinite groups and appropriately chosen convolutional kernels, already two-parameter families of convolutional neural networks have an infinite VC dimension, despite being invariant to the action of an infinite group.
