1 citations · 1 across the 2 of their papers we have counts for
3 papers · 1 filter
A Divide-and-Conquer Strategy for Hard-Label Extraction of Deep Neural Networks via Side-Channel Attacks
Benoit Coqueret, Mathieu Carbone, Olivier Sentieys +1
During the past decade, Deep Neural Networks (DNNs) proved their value on a large variety of subjects. However despite their high value and public accessibility, the protection of…
AdaQAT: Adaptive Bit-Width Quantization-Aware Training
Cédric Gernigon, Silviu-Ioan Filip, Olivier Sentieys +2
Large-scale deep neural networks (DNNs) have achieved remarkable success in many application scenarios. However, high computational complexity and energy costs of modern DNNs make…
A Stochastic Rounding-Enabled Low-Precision Floating-Point MAC for DNN Training
Sami Ben Ali, Silviu-Ioan Filip, Olivier Sentieys
Training Deep Neural Networks (DNNs) can be computationally demanding, particularly when dealing with large models. Recent work has aimed to mitigate this computational challenge b…