3 papers
cs.CR2026
TrustErase: Auditable Instant Machine Unlearning with Passport-Embedded Representations
Rutger Hendrix, Leonardo G. Russo, Concetto Spampinato +2
The demand for privacy-compliant AI has amplified the need for machine unlearning; yet, existing retraining or distillation-based methods remain unverifiable and computationally co…
cs.LG2025
Pre-Forgettable Models: Prompt Learning as a Native Mechanism for Unlearning
Rutger Hendrix, Giovanni Patanè, Leonardo G. Russo +5
Foundation models have transformed multimedia analysis by enabling robust and transferable representations across diverse modalities and tasks. However, their static deployment con…
cs.CV2024
Evidential Federated Learning for Skin Lesion Image Classification
Rutger Hendrix, Federica Proietto Salanitri, Concetto Spampinato +2
We introduce FedEvPrompt, a federated learning approach that integrates principles of evidential deep learning, prompt tuning, and knowledge distillation for distributed skin lesio…