I'm reading the paper (http://proceedings.mlr.press/v9/glorot10a/glorot10a.pdf) from Glorot and Bengio. There is something that I don't understand at the abstract section on page 1.
"Training may be more difficult when the singular values of the Jacobian associated with each layer are far from 1"
Why is the singular value of the Jacobian important for training?
Why is the singular value being far from 1 difficult for training?