Hint: Stay until the end of the video for an adversarial attack compilation!
🤔 Ever wondered what adversarial attacks are? What FGSM, the Fast Gradient Sign method, is? What the difference between Adversarial Machine Learning and Generative Adversarial Networks is? If yes, you have found the right video for you!
➡️ AI Coffee Break Merch! 🛍️ [ Ссылка ]

Outline:
* 00:00 Difference between GANs and Adversarial ML
* 01:04 Noise Attack
* 01:52 Fast Gradient Sign Method (FGSM)
* 03:53 Targeted vs Untargeted
* 04:53 White box vs Black box
* 05:38 Adversarial examples
* 06:32 Defenses against adversarial attacks
* 08:46 Aversarial examples COMPILATION

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🔥 Optionally, pay us a coffee to boost our Coffee Bean production! ☕
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For all the juicy details about the topic, check out this video @stanfordengineering : [ Ссылка ]

📄 Goodfellow, Ian J., Jonathon Shlens, and Christian Szegedy. "Explaining and harnessing adversarial examples." arXiv preprint arXiv:1412.6572 (2014). [ Ссылка ]

📄 Thys, Simen, Wiebe Van Ranst, and Toon Goedemé. "Fooling automated surveillance cameras: adversarial patches to attack person detection." In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 0-0. 2019. [ Ссылка ]

📄 Belinkov, Yonatan, and Yonatan Bisk. "Synthetic and natural noise both break neural machine translation." arXiv preprint arXiv:1711.02173 (2017). [ Ссылка ]


🔗 Links:
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#AICoffeeBreak #MsCoffeeBean #AdversarialML #MachineLearning #AI #research

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