most citedCoordination-free Decentralised Federated Learning on Complex Networks: Overcoming Heterogeneity

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

physics.soc-ph2024

Disentangling degree and tie strength heterogeneity in egocentric social networks

Sara Heydari, Gerardo Iñiguez, János Kertész +1

The structure of personal networks reflects how we organise and maintain social relationships. The distribution of tie strengths in personal networks is heterogeneous, with a few c…

cs.LG2023★ 2 cited

Coordination-free Decentralised Federated Learning on Complex Networks: Overcoming Heterogeneity

Lorenzo Valerio, Chiara Boldrini, Andrea Passarella +3

Federated Learning (FL) is a well-known framework for successfully performing a learning task in an edge computing scenario where the devices involved have limited resources and in…