4 papers
Tackling Heterogeneity in Federated Learning via Variance-Reduced Boltzmann Sampling within Homogeneous Social Coalitions
Alessandro Licciardi, Roberta Raineri, Anton Proskurnikov +2
Federated Learning (FL) enables privacy-preserving collaborative model training, but its effectiveness is often limited by client data heterogeneity. We introduce a client-selectio…
Controlling a Social Network of Individuals with Coevolving Actions and Opinions
Roberta Raineri, Mengbin Ye, Lorenzo Zino
In this paper, we consider a population of individuals who have actions and opinions, which coevolve, mutually influencing one another on a complex network structure. In particular…
Optimal selection of the most informative nodes for a noisy DeGroot model with stubborn agents
Roberta Raineri, Giacomo Como, Fabio Fagnani
Finding the optimal subset of individuals to observe in order to obtain the best estimate of the average opinion of a society is a crucial problem in a wide range of applications,…
FJ-MM: The Friedkin-Johnsen Opinion Dynamics Model with Memory and Higher-Order Neighbors
Roberta Raineri, Lorenzo Zino, Anton Proskurnikov
The Friedkin-Johnsen (FJ) model has been extensively explored and validated, spanning applications in social science, systems and control, game theory, and algorithmic research. In…