training deep leaning models early stopping is quite non-invasivein the sense that it does not require any changes to the model it is also inexpensiveas it only requires storing the parameters of the model (the best so far on the validation setit can also be combined easily with other regularization techniques figure - early stopping restricts norm penalties norm penalties are common form of regularization in deep learning (and machine learning in generalthe idea is simply to add term (thto the loss function of neural network (refer to )where typically represents either the norm or the norm and th represents the parameters/weights of the network thusthe regularized loss function becomes lfnn(xth)ya (thinstead of just lfnn(xth)ynote that the term is the regularization parameter