I have been reading about Generative Adversarial Networks (GANs) and was wondering if it would make sense to train a generator function only to use it for creating more training data.
In a scenario where I don't have enough training data to build a robust classifier, can I use this limited data to train a generator that'll produce samples good enough to improve the accuracy of my discriminator (classifier)?