4 papers
Explanations Leak: Membership Inference with Differential Privacy and Active Learning Defense
Fatima Ezzeddine, Osama Zammar, Silvia Giordano +1
Counterfactual explanations (CFs) are increasingly integrated into Machine Learning as a Service (MLaaS) systems to improve transparency; however, ML models deployed via APIs are a…
Fair Recourse for All: Ensuring Individual and Group Fairness in Counterfactual Explanations
Fatima Ezzeddine, Obaida Ammar, Silvia Giordano +1
Explainable Artificial Intelligence (XAI) is becoming increasingly essential for enhancing the transparency of machine learning (ML) models. Among the various XAI techniques, count…
Fair-FLIP: Fair Deepfake Detection with Fairness-Oriented Final Layer Input Prioritising
Tomasz Szandala, Fatima Ezzeddine, Natalia Rusin +2
Artificial Intelligence-generated content has become increasingly popular, yet its malicious use, particularly the deepfakes, poses a serious threat to public trust and discourse.…
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…