54 citations · 64 across the 4 of their papers we have counts for
12 papers
Beyond permutation equivariance in graph networks
Emma Slade, Francesco Farina
In this draft paper, we introduce a novel architecture for graph networks which is equivariant to the Euclidean group in -dimensions. The model is designed to work with graph ne…
Distributed Constraint-Coupled Optimization via Primal Decomposition over Random Time-Varying Graphs
Andrea Camisa, Francesco Farina, Ivano Notarnicola +1
The paper addresses large-scale, convex optimization problems that need to be solved in a distributed way by agents communicating according to a random time-varying graph. Specific…
Distributed Personalized Gradient Tracking with Convex Parametric Models
Ivano Notarnicola, Andrea Simonetto, Francesco Farina +1
We present a distributed optimization algorithm for solving online personalized optimization problems over a network of computing and communicating nodes, each of which linked to a…
On the Linear Convergence Rate of the Distributed Block Proximal Method
Francesco Farina, Giuseppe Notarstefano
The recently developed Distributed Block Proximal Method, for solving stochastic big-data convex optimization problems, is studied in this paper under the assumption of constant st…
Asynchronous Distributed Learning from Constraints
Francesco Farina, Stefano Melacci, Andrea Garulli +1
In this paper, the extension of the framework of Learning from Constraints (LfC) to a distributed setting where multiple parties, connected over the network, contribute to the lear…
DISROPT: a Python Framework for Distributed Optimization
Francesco Farina, Andrea Camisa, Andrea Testa +2
In this paper we introduce DISROPT, a Python package for distributed optimization over networks. We focus on cooperative set-ups in which an optimization problem must be solved by…