Differentially Private Data Generative Models

6 Dec 2018Qingrong ChenChong XiangMinhui XueBo LiNikita BorisovDali KaarfarHaojin Zhu

Deep neural networks (DNNs) have recently been widely adopted in various applications, and such success is largely due to a combination of algorithmic breakthroughs, computation resource improvements, and access to a large amount of data. However, the large-scale data collections required for deep learning often contain sensitive information, therefore raising many privacy concerns... (read more)

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