Certified Robustness Explained
Hadi and Tim delve into the world of certified defenses for neural networks, discussing the difference between empirical and certified defenses. Hadi sheds light on the importance of finding proofs to ensure robustness against attacks, offering insights into the complexities of certifying neural networks.In this clip
From this podcast
Machine Learning Street Talk (MLST)
#52 - Unadversarial Examples (Hadi Salman, MIT)
Related Questions
How can we defend against adversarial attacks on machine learning models as discussed in the episode #52 - Unadversarial Examples (Hadi Salman, MIT) and the clip Neural Network Features?
How can we defend against adversarial attacks on machine learning models?
What are adversarial attacks on machine learning models as discussed in the episode #52 - Unadversarial Examples (Hadi Salman, MIT) and the clip Neural Network Features?