collaborators

5 papers

cs.LG2026

The Gaussian-Head OFL Family: One-Shot Federated Learning from Client Global Statistics

Fabio Turazza, Marco Picone, Marco Mamei

Classical Federated Learning relies on a multi-round iterative process of model exchange and aggregation between server and clients, with high communication costs and privacy risks…

cs.AI2026

Digital Twins & ZeroConf AI: Structuring Automated Intelligent Pipelines for Industrial Applications

Marco Picone, Fabio Turazza, Matteo Martinelli +1

The increasing complexity of Cyber-Physical Systems (CPS), particularly in the industrial domain, has amplified the challenges associated with the effective integration of Artifici…

cs.LG2026

Blockchain Federated Learning for Sustainable Retail: Reducing Waste through Collaborative Demand Forecasting

Fabio Turazza, Alessandro Neri, Marcello Pietri +3

Effective demand forecasting is crucial for reducing food waste. However, data privacy concerns often hinder collaboration among retailers, limiting the potential for improved pred…

cs.CR2026

FedBGS: A Blockchain Approach to Segment Gossip Learning in Decentralized Systems

Fabio Turazza, Marcello Pietri, Marco Picone +1

Privacy-Preserving Federated Learning (PPFL) is a Decentralized machine learning paradigm that enables multiple participants to collaboratively train a global model without sharing…

cs.LG2026

Forecasting Energy Availability in Local Energy Communities via LSTM Federated Learning

Fabio Turazza, Marcello Pietri, Natalia Selini Hadjidimitriou +1

Local Energy Communities are emerging as crucial players in the landscape of sustainable development. A significant challenge for these communities is achieving self-sufficiency th…