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cs.LG2023
Training generative models from privatized data
Daria Reshetova, Wei-Ning Chen, Ayfer Özgür
Local differential privacy is a powerful method for privacy-preserving data collection. In this paper, we develop a framework for training Generative Adversarial Networks (GANs) on…
cs.LG2021
Understanding Entropic Regularization in GANs
Daria Reshetova, Yikun Bai, Xiugang Wu +1
Generative Adversarial Networks are a popular method for learning distributions from data by modeling the target distribution as a function of a known distribution. The function, o…