2 papers
cs.LG2021
Neural Architecture Search via Bregman Iterations
Leon Bungert, Tim Roith, Daniel Tenbrinck +1
We propose a novel strategy for Neural Architecture Search (NAS) based on Bregman iterations. Starting from a sparse neural network our gradient-based one-shot algorithm gradually…
cs.LG2020
Dynamically Sampled Nonlocal Gradients for Stronger Adversarial Attacks
Leo Schwinn, An Nguyen, René Raab +4
The vulnerability of deep neural networks to small and even imperceptible perturbations has become a central topic in deep learning research. Although several sophisticated defense…