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cs.LG2025
Exploiting Edge Features for Transferable Adversarial Attacks in Distributed Machine Learning
Giulio Rossolini, Fabio Brau, Alessandro Biondi +2
As machine learning models become increasingly deployed across the edge of internet of things environments, a partitioned deep learning paradigm in which models are split across mu…
cs.LG2023
1-Lipschitz Layers Compared: Memory, Speed, and Certifiable Robustness
Bernd Prach, Fabio Brau, Giorgio Buttazzo +1
The robustness of neural networks against input perturbations with bounded magnitude represents a serious concern in the deployment of deep learning models in safety-critical syste…