Adversarial Attacks and Defenses. The Dimpled Manifold Hypothesis. David Stutz from DeepMind
🎙️ Interview with David Stutz from Google DeepMind at the 10th HLF. We spoke about adversarial attacks and defenses for neural networks and about hypotheses that aim to explain their existence.
The HLF is an annual gathering of 200 young researchers from math and computer science and laureates of the most prestigious awards in these two fields, such as the ACM Turing Award, ACM Prize in Computing, Fields Medal, IMU Abacus Medal, Nevanlinna Prize (https://www.heidelberg-laureate-forum....
I attended the last year’s HLF as a young researcher and this year as a press member. The best things for me at the HLF remain the lengthy coffee breaks and social events at incredible locations such as the boat on the Neckar River on which we were at the interview which you’ve just seen on this video! I hope you found this discussion with David Stutz about adversarial attacks and defences as interesting as Ms. Coffee Bean did.
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📚 And check out David’s blog post for impressions and a sample application: https://davidstutz.de/my-impressions-...
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Outline:
00:00 What are adversarial attacks on Neural Networks?
01:20 Research on adversarial attacks is easier to publish than Defenses!?
05:07 The Dimpled Manifold Hypothesis
08:05 Why else do adversarial examples exist?
11:00 Where was this interview taken? About the HLF.
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Music 🎵 : Boom Bap Flick – Quincas Moreira
Video editing: Nils Trost
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