Bottou. Wasserstein gener- ative adversarial networks. In Proc. of International Confer- ence on Machine Learning, pages 214–223, August 2017. [3] A. Arsalan Soltani, H. Huang, J. Wu, T. D. Kulkarni, and J. B.
Furthermore, this paper also modifies the loss function to improve the performance in the case of data imbalance, and introduces the Wasserstein distance to optimize the adversarial training process. The proposed method is experimentally verified on Case Western Reserve University, Jiangnan University, ...