Finding Solutions to Generative Adversarial Privacy

4 Oct 2018 Dae Hyun Kim Taeyoung Kong Seungbin Jeong

We present heuristics for solving the maximin problem induced by the generative adversarial privacy setting for linear and convolutional neural network (CNN) adversaries. In the linear adversary setting, we present a greedy algorithm for approximating the optimal solution for the privatizer, which performs better as the number of instances increases... (read more)

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