10 citations · 19 across the 5 of their papers we have counts for
4 papers · 1 filter
PUMA: margin-based data pruning
Javier Maroto, Pascal Frossard
Deep learning has been able to outperform humans in terms of classification accuracy in many tasks. However, to achieve robustness to adversarial perturbations, the best methodolog…
Adversarial training with informed data selection
Marcele O. K. Mendonça, Javier Maroto, Pascal Frossard +1
With the increasing amount of available data and advances in computing capabilities, deep neural networks (DNNs) have been successfully employed to solve challenging tasks in vario…
Maximum Likelihood Distillation for Robust Modulation Classification
Javier Maroto, Gérôme Bovet, Pascal Frossard
Deep Neural Networks are being extensively used in communication systems and Automatic Modulation Classification (AMC) in particular. However, they are very susceptible to small ad…
On the benefits of knowledge distillation for adversarial robustness
Javier Maroto, Guillermo Ortiz-Jiménez, Pascal Frossard
Knowledge distillation is normally used to compress a big network, or teacher, onto a smaller one, the student, by training it to match its outputs. Recently, some works have shown…