training the teacher network so the teacher network is evaluated on the validation set performance of the student network after it updated as parameters to theta t plus 1 so the way that this reward is propagated back into the teachers parameters Phi because you have to take the derivative of how much each of these five parameters and their labels and data points impacts the gradient of the student network to change it in the direction of this validation loss it's difficult to completely derive this idea of gradient