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cs.LG2026
Adaptive Regularization for Sparsity Control in Bregman-Based Optimizers
Ahmad Aloradi, Tim Roith, Emanuël A. P. Habets +1
Sparse training reduces the memory and computational costs of deep neural networks. However, sparse optimization methods, e.g., those adding an penalty, often control spar…
cs.LG2025
Adversarial flows: A gradient flow characterization of adversarial attacks
Lukas Weigand, Tim Roith, Martin Burger
A popular method to perform adversarial attacks on neuronal networks is the so-called fast gradient sign method and its iterative variant. In this paper, we interpret this method a…