12 citations · 18 across the 12 of their papers we have counts for
5 papers · 1 filter
Adversarial Attacks Leverage Interference Between Features in Superposition
Edward Stevinson, Lucas Prieto, Melih Barsbey +1
Why do adversarial examples exist, and why do they transfer between models? Existing explanations appeal to high-dimensional geometry, non-robust patterns in the input, and decisio…
Large Learning Rates Simultaneously Achieve Robustness to Spurious Correlations and Compressibility
Melih Barsbey, Lucas Prieto, Stefanos Zafeiriou +1
Robustness and resource-efficiency are two highly desirable properties for modern machine learning models. However, achieving them jointly remains a challenge. In this paper, we id…
On the Interaction of Compressibility and Adversarial Robustness
Melih Barsbey, Antônio H. Ribeiro, Umut Şimşekli +1
As demands for resource efficiency and safety in modern neural networks intensify, substantial research effort has gone into model compression and adversarial robustness. Yet despi…
Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise
Thanh Dang, Melih Barsbey, A K M Rokonuzzaman Sonet +3
Understanding the generalization properties of optimization algorithms under heavy-tailed noise has gained growing attention. However, the existing theoretical results mainly focus…
Grokking at the Edge of Numerical Stability
Lucas Prieto, Melih Barsbey, Pedro A. M. Mediano +1
Grokking, the sudden generalization that occurs after prolonged overfitting, is a surprising phenomenon challenging our understanding of deep learning. Although significant progres…