Litcius/Paper detail

Data Privacy and Trustworthy Machine Learning

Martin Strobel, Reza Shokri

2022IEEE Security & Privacy36 citationsDOIOpen Access PDF

Abstract

The privacy risks of machine learning models is a major concern when training them on sensitive and personal data. We discuss the tradeoffs between data privacy and the remaining goals of trustworthy machine learning (notably, fairness, robustness, and explainability).

Topics & Concepts

TrustworthinessComputer scienceRobustness (evolution)Information privacyInternet privacyComputer securityMachine learningArtificial intelligenceChemistryBiochemistryGenePrivacy-Preserving Technologies in DataAdversarial Robustness in Machine LearningArtificial Intelligence in Healthcare and Education
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