[D] GAN training

Am trying to train GANs for oversampling a minority text class (am feeding it only the minority class), but the results dont seem to improve much (AUC only improves by .03 so far). while basic oversampling techniques like SMOTE gives way better results. also am using a vector representation for the whole text instead of word embedding(same used for SMOTE), i tried different architectures with CNN.

is there any tricks maybe in training the discriminator and generator ? i can't …

auc basic embedding gan gans machinelearning oversampling representation smote text training vector word