Better accuracy with quantified privacy: representations learned via reconstructive adversarial network

ICLR 2019 Sicong LiuAnshumali ShrivastavaJunzhao DuLin Zhong

The remarkable success of machine learning, especially deep learning, has produced a variety of cloud-based services for mobile users. Such services require an end user to send data to the service provider, which presents a serious challenge to end-user privacy... (read more)

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