11 citations · 18 across the 2 of their papers we have counts for
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cs.LG2020
FADER: Fast Adversarial Example Rejection
Francesco Crecchi, Marco Melis, Angelo Sotgiu +2
Deep neural networks are vulnerable to adversarial examples, i.e., carefully-crafted inputs that mislead classification at test time. Recent defenses have been shown to improve adv…
cs.LG2020★ 7 cited
Perplexity-free Parametric t-SNE
Francesco Crecchi, Cyril de Bodt, Michel Verleysen +2
The t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm is a ubiquitously employed dimensionality reduction (DR) method. Its non-parametric nature and impressive efficacy…