no code implementations • 9 Apr 2024 • Fatima Ezzeddine, Mirna Saad, Omran Ayoub, Davide Andreoletti, Martin Gjoreski, Ihab Sbeity, Marc Langheinrich, Silvia Giordano
Anomaly detection (AD), also referred to as outlier detection, is a statistical process aimed at identifying observations within a dataset that significantly deviate from the expected pattern of the majority of the data.
no code implementations • 4 Apr 2024 • Fatima Ezzeddine, Omran Ayoub, Silvia Giordano
To this end, we first propose a novel MEA methodology based on Knowledge Distillation (KD) to enhance the efficiency of extracting a substitute model of a target model exploiting CFs.
3 code implementations • 17 Oct 2022 • Fatima Ezzeddine, Luca Luceri, Omran Ayoub, Ihab Sbeity, Gianluca Nogara, Emilio Ferrara, Silvia Giordano
The detection of state-sponsored trolls operating in influence campaigns on social media is a critical and unsolved challenge for the research community, which has significant implications beyond the online realm.