2020
Learning Semi-Supervised Anonymized Representations by Mutual Information
ICASSP 2020accepted
This paper addresses the problem of removing from a set of data (here images) a given private information, while still allowing other utilities on the processed data. This is obtained by training concurrently a GAN-like discriminator and an autoencoder. The optimization of the resulting structure in…