September 2, 2022

Machine Learning Robustness and Security

September 2, 2022  •  1 min  • 141 words  •


Relevant Projects

Hierarchical Robustness

    DNNs are susceptible to adversarial examples. Fortunately, objects tend to have invariant salient features. Applying invariants to the classification task hierarchically makes robustness and accuracy feasible together.


    Advances in deep learning have made face recognition technologies and surveillance pervasive. Face-Off is a privacy-preserving framework that introduces strategic perturbations to the user's face to prevent it from being correctly recognized.

Face Obfuscation Fairness

    A recent, popular approach to address face recognition privacy concerns is to employ evasion attacks against the DNNs powering face recognition systems. This dependence of face obfuscation on DNNs, which are known to be unfair in the context of face recognition, surfaces the question of demographic fairness.
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