G2R Bound: A Generalization Bound for Supervised Learning from GAN-Synthetic Data

29 May 2019Fu-Chieh ChangHao-Jen WangChun-Nan ChouEdward Y. Chang

Performing supervised learning from the data synthesized by using Generative Adversarial Networks (GANs), dubbed GAN-synthetic data, has two important applications. First, GANs may generate more labeled training data, which may help improve classification accuracy... (read more)

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