4 papers
DecHW: Heterogeneous Decentralized Federated Learning Exploiting Second-Order Information
Adnan Ahmad, Chiara Boldrini, Lorenzo Valerio +2
Decentralized Federated Learning (DFL) is a serverless collaborative machine learning paradigm where devices collaborate directly with neighbouring devices to exchange model inform…
EARL: Energy-Aware Optimization of Liquid State Machines for Pervasive AI
Zain Iqbal, Lorenzo Valerio
Pervasive AI increasingly depends on on-device learning systems that deliver low-latency and energy-efficient computation under strict resource constraints. Liquid State Machines (…
DODO: Causal Structure Learning with Budgeted Interventions
Matteo Gregorini, Chiara Boldrini, Lorenzo Valerio
Artificial Intelligence has achieved remarkable advancements in recent years, yet much of its progress relies on identifying increasingly complex correlations. Enabling causality a…
The Built-In Robustness of Decentralized Federated Averaging to Bad Data
Samuele Sabella, Chiara Boldrini, Lorenzo Valerio +2
Decentralized federated learning (DFL) enables devices to collaboratively train models over complex network topologies without relying on a central controller. In this setting, loc…