DoppelGANger: A new tool for sharing time series data with GANs
Guest Post: New tool allows for sharing sensitive time series data.
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Zinan Lin is a PhD student at Carnegie Mellon University, advised by Giulia Fanti and Vyas Sekar. His research interests are the theoretical foundations of generative adversarial networks (GANs) and their applications in networking, systems, security, and privacy. He is a recipient of Siemens FutureMakers Fellowship, CMU Presidential Fellowship, and Cylab Presidential Fellowship.
By Zinan Lin on 18 Dec 2020
Guest Post: New tool allows for sharing sensitive time series data.