Learning to Succeed while Teaching to Fail: Privacy in Closed Machine Learning Systems

23 May 2017Jure SokolicQiang QiuMiguel R. D. RodriguesGuillermo Sapiro

Security, privacy, and fairness have become critical in the era of data science and machine learning. More and more we see that achieving universally secure, private, and fair systems is practically impossible... (read more)

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