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A geometric perspective on adversarial perturbations
Student-Run Geometry/Topology SeminarSpeaker: | Tommy Hogan, UC Davis |
Related Webpage: | https://www.math.ucdavis.edu/~tahogan/ |
Location: | 2112 MSB |
Start time: | Thu, Oct 18 2018, 12:10PM |
Adversarial examples are slightly perturbed images resembling natural images but maliciously crafted to fool pre-trained image classifiers (usually a deep neural network). We will discuss some geometric explanations on why these examples exist, as well as some algorithms for finding them.