56 citations · 233 across the 22 of their papers we have counts for
3 papers · 1 filter
Machine Unlearning for the XGBoost Model with Network Intrusion Datasets
Diana Magalhães, Eva Maia, João Vitorino +1
Machine Unlearning (MU) has emerged as an important technique for removing specific data points from trained models without requiring full retraining. However, most existing MU res…
Evaluating Local Explainability Metrics for Machine Learning Models on Tabular Data
Tomás Pereira, João Vitorino, Eva Maia +1
Despite the wide use of explainability techniques to attempt to understand the behavior of Artificial Intelligence (AI), the generated explanations may not always be reliable. An e…
Machine Learning Transferability for Malware Detection
César Vieira, João Vitorino, Eva Maia +1
Malware continues to be a predominant operational risk for organizations, especially when obfuscation techniques are used to evade detection. Despite the ongoing efforts in the dev…