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AsynDGAN structure. It is a Single-Generator Multi-Discrminator GAN structure

Generative Adversarial Networks (GANs) are an emerging methodology to synthesize data, ranging from images, to text, and to tables. The key components of GANs are training two competing neural networks, i.e., generator and discriminator, where the former iteratively generates synthetic data and the latter judges its quality. During the training process, the discriminator needs to access the original data and provide feedback to the generator by comparing it with the generated data. However, such a privilege of direct data access may no longer be taken for granted due to the ever increasing concern for data privacy. For instance, training a…

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