2 papers
cs.LG2026
Discovering Collaboration from Novelty: Random Network Distillation for Clustered Federated Learning
Davide Domini, Gianluca Aguzzi, Ivana Dusparic +2
Federated Learning often suffers under non-independently and identically distributed data, where a single global model may fail to represent the diversity of client distributions.…
cs.DC2026
Flexible Distributed Particle Filtering for the Internet of Things via Aggregate Computing
Angela Cortecchia, Davide Domini, Giovanni Ciatto +3
State estimation from uncertain, distributed observations is central in many cyber-physical applications. While Distributed Particle Filtering (DPF) algorithms address nonlinear an…