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cs.CV2021★ 1 cited
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients
Alessandro Cappelli, Julien Launay, Laurent Meunier +2
Robustness to adversarial attacks is typically obtained through expensive adversarial training with Projected Gradient Descent. Here we introduce ROPUST, a remarkably simple and ef…
cs.CV2021★ 9 cited
Adversarial Robustness by Design through Analog Computing and Synthetic Gradients
Alessandro Cappelli, Ruben Ohana, Julien Launay +3
We propose a new defense mechanism against adversarial attacks inspired by an optical co-processor, providing robustness without compromising natural accuracy in both white-box and…