#040 – Adversarial Examples (Dr. Nicholas Carlini, Dr. Wieland Brendel, Florian Tramèr)

Pod version; https://anchor.fm/machinelearningstreettalk/episodes/040—Adversarial-Examples-Dr–Nicholas-Carlini–Dr–Wieland-Brendel–Florian-Tramr-epo5qr Adversarial examples have attracted significant attention in machine learning, but the reasons for their existence and pervasiveness remain unclear. there’s good reason to believe neural networks look at very different features than we would have expected. As articulated in the 2019 “features not bugs” paper Adversarial examples can be directly attributed to […]