In this task, you are given the abstract of a research paper. Your task is to generate a summary of this abstract. Your summary should not be very short, but it's better if it's not more than 30 words.

We prove bounds on the generalization error of convolutional networks.
The bounds are in terms of the training loss, the number of
parameters, the Lipschitz constant of the loss and the distance from
the weights to the initial weights. They are independent of the
number of pixels in the input, and the height and width of hidden
feature maps. We present experiments with CIFAR-10, along with varying
hyperparameters of a deep convolutional network, comparing our bounds
with practical generalization gaps.
We prove generalization bounds for convolutional neural networks that take account of weight-tying