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4. Learning Semi-Supervised Anonymized Representations By Mutual Information

Learning Semi-Supervised Anonymized Representations By Mutual Information

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IEEE ICASSP 2020 Virtual Conference May 2020

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. T

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Learning Semi-Supervised Anonymized Representations By Mutual Information

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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. T