5 citations · 7 across the 7 of their papers we have counts for
7 papers
On the interplay of Explainability, Privacy and Predictive Performance with Explanation-assisted Model Extraction
Fatima Ezzeddine, Rinad Akel, Ihab Sbeity +3
Machine Learning as a Service (MLaaS) has gained important attraction as a means for deploying powerful predictive models, offering ease of use that enables organizations to levera…
A longitudinal analysis of misinformation, polarization and toxicity on Bluesky after its public launch
Gianluca Nogara, Erfan Samieyan Sahneh, Matthew R. DeVerna +5
Bluesky is a decentralized, Twitter-like social media platform that has rapidly gained popularity. Following an invite-only phase, it officially opened to the public on February 6t…
The Dawn of Decentralized Social Media: An Exploration of Bluesky's Public Opening
Erfan Samieyan Sahneh, Gianluca Nogara, Matthew R. DeVerna +5
Bluesky is a Twitter-like decentralized social media platform that has recently grown in popularity. After an invite-only period, it opened to the public worldwide on February 6th,…
The Magic XRoom: A Flexible VR Platform for Controlled Emotion Elicitation and Recognition
S. M. Hossein Mousavi, Matteo Besenzoni, Davide Andreoletti +2
Affective computing has recently gained popularity, especially in the field of human-computer interaction systems, where effectively evoking and detecting emotions is of paramount…
Differential Privacy for Anomaly Detection: Analyzing the Trade-off Between Privacy and Explainability
Fatima Ezzeddine, Mirna Saad, Omran Ayoub +5
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 expec…
Liquid Neural Network-based Adaptive Learning vs. Incremental Learning for Link Load Prediction amid Concept Drift due to Network Failures
Omran Ayoub, Davide Andreoletti, Aleksandra Knapińska +6
Adapting to concept drift is a challenging task in machine learning, which is usually tackled using incremental learning techniques that periodically re-fit a learning model levera…