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Machine Learning (ML) models are increasingly deployed in the wild to perform a wide range of tasks.
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Privacy-preserving visual learning using doubly permuted homomorphic encryption
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Faceless person recognition; privacy implications in social media
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Art of singular vectors and universal adversarial perturbations
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Deep mutual learning
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Ml-leaks: Model and data independent membership inference attacks and defenses on machine learning models
A. Salem, Y. Zhang, M. Humbert, M. Fritz, and M. Backes · 2019
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