3 papers
cs.NE2026
STAER: Temporal Aligned Rehearsal for Continual Spiking Neural Network
Matteo Gianferrari, Omayma Moussadek, Riccardo Salami +4
Spiking Neural Networks (SNNs) are inherently suited for continuous learning due to their event-driven temporal dynamics; however, their application to Class-Incremental Learning (…
cs.LG2025
Intrinsic Training Signals for Federated Learning Aggregation
Cosimo Fiorini, Matteo Mosconi, Pietro Buzzega +2
Federated Learning (FL) enables collaborative model training across distributed clients while preserving data privacy. While existing approaches for aggregating client-specific cla…
cs.CY2025
A Toolkit for Compliance, a Toolkit for Justice: Drawing on Cross-sectoral Expertise to Develop a Pro-justice EU AI Act Toolkit
Tomasz Hollanek, Yulu Pi, Cosimo Fiorini +3
The introduction of the AI Act in the European Union presents the AI research and practice community with a set of new challenges related to compliance. While it is certain that AI…