429 citations · 664 across the 34 of their papers we have counts for
3 papers · 1 filter
Aggregated f-average Neural Network applied to Few-Shot Class Incremental Learning
Mathieu Vu, Emilie Chouzenoux, Ismail Ben Ayed +1
Ensemble learning leverages multiple models (i.e., weak learners) on a common machine learning task to enhance prediction performance. Basic ensembling approaches average the weak…
Model-Agnostic Few-Shot Open-Set Recognition
Malik Boudiaf, Etienne Bennequin, Myriam Tami +4
We tackle the Few-Shot Open-Set Recognition (FSOSR) problem, i.e. classifying instances among a set of classes for which we only have few labeled samples, while simultaneously dete…
Adversarial Robustness via Fisher-Rao Regularization
Marine Picot, Francisco Messina, Malik Boudiaf +3
Adversarial robustness has become a topic of growing interest in machine learning since it was observed that neural networks tend to be brittle. We propose an information-geometric…