Adversarial Examples Explained
Adversarial examples are a broad phenomenon affecting various model types, including deep neural networks and decision trees. The process of creating these examples involves subtly manipulating inputs to mislead models without noticeable changes to human observers. Interestingly, defenses against such attacks can be model-agnostic, focusing on input transformations to mitigate noise.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Security and Safety in AI: Adversarial Examples, Bias and Trust with Moustapha Cissé - #108
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