20 citations · 35 across the 10 of their papers we have counts for
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stat.AP2019★ 20 cited
Anomaly and Novelty detection for robust semi-supervised learning
Andrea Cappozzo, Francesca Greselin, Thomas Brendan Murphy
Three important issues are often encountered in Supervised and Semi-Supervised Classification: class-memberships are unreliable for some training units (label noise), a proportion…
stat.AP2019★ 12 cited
A robust approach to model-based classification based on trimming and constraints
Andrea Cappozzo, Francesca Greselin, Thomas Brendan Murphy
In a standard classification framework a set of trustworthy learning data are employed to build a decision rule, with the final aim of classifying unlabelled units belonging to the…