21 citations · 24 across the 5 of their papers we have counts for
5 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…
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…
Exposing Influence Campaigns in the Age of LLMs: A Behavioral-Based AI Approach to Detecting State-Sponsored Trolls
Fatima Ezzeddine, Luca Luceri, Omran Ayoub +4
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 impl…
Combining the analytical hierarchy process and the genetic algorithm to solve the timetable problem
Ihab Sbeity, Mohamed Dbouk, Habib Kobeissi
The main problems of school course timetabling are time, curriculum, and classrooms. In addition there are other problems that vary from one institution to another. This paper is i…
Generating a Performance Stochastic Model from UML Specifications
Ihab Sbeity, Leonardo Brenner, Mohamed Dbouk
Since its initiation by Connie Smith, the process of Software Performance Engineering (SPE) is becoming a growing concern. The idea is to bring performance evaluation into the soft…