I've read the ResNet paper (https://arxiv.org/pdf/1512.03385.pdf)
It looks like they say like overfitting is cause of it in subsection ("Exploring Over 1000 layers.")
The testing result of this 1202-layer network is worse than that of our 110-layer network. We argue that this is because of overfitting
I think those are related like degradation causes overfitting, because it is like fitting too complex functions and is same as fitting too many layers. If that is correct than I do know know what type of overfitting is meant when the 1000+ layers are trained.
How to understand difference between those 2 concepts?