198 citations · 481 across the 31 of their papers we have counts for
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cs.LG2022★ 5 cited
On the Privacy Properties of GAN-generated Samples
Zinan Lin, Vyas Sekar, Giulia Fanti
The privacy implications of generative adversarial networks (GANs) are a topic of great interest, leading to several recent algorithms for training GANs with privacy guarantees. By…
cs.LG2022
RareGAN: Generating Samples for Rare Classes
Zinan Lin, Hao Liang, Giulia Fanti +1
We study the problem of learning generative adversarial networks (GANs) for a rare class of an unlabeled dataset subject to a labeling budget. This problem is motivated from practi…