3 papers
cs.LG2025
Lattice Climber Attack: Adversarial attacks for randomized mixtures of classifiers
Lucas Gnecco-Heredia, Benjamin Negrevergne, Yann Chevaleyre
Finite mixtures of classifiers (a.k.a. randomized ensembles) have been proposed as a way to improve robustness against adversarial attacks. However, existing attacks have been show…
cs.LG2023
Adversarial attacks for mixtures of classifiers
Lucas Gnecco Heredia, Benjamin Negrevergne, Yann Chevaleyre
Mixtures of classifiers (a.k.a. randomized ensembles) have been proposed as a way to improve robustness against adversarial attacks. However, it has been shown that existing attack…
cs.LG2023
Training Normalizing Flows with the Precision-Recall Divergence
Alexandre Verine, Benjamin Negrevergne, Muni Sreenivas Pydi +1
Generative models can have distinct mode of failures like mode dropping and low quality samples, which cannot be captured by a single scalar metric. To address this, recent works p…