loss term which minimizes the entropy for the unlabeled data mix match applies sharpening function to reduce the entropy of the label distribution and this is done by adjusting the temperature of the categorical distribution now the last is the mix-up a mix-up is a recently proposed method for training deep neural networks where additional samples are generated during training by convexly combining random pairs of images and their associated labels by doing so mixer regularizes the neural network to favor simple linear behavior