One minimizes mean square error
The other minimizes a weighted sum of squared errors and squared weights
The latter is typically used to prevent overtraining an overfit net without using a validation subset.
Therefore it is most useful for small datasets to keep the training subset as large as feasible.
Hope this helps.
Thank you for formally accepting my answer
Greg
