54 citations · 144 across the 14 of their papers we have counts for
9 papers · 1 filter
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…
GTAdam: Gradient Tracking with Adaptive Momentum for Distributed Online Optimization
Guido Carnevale, Francesco Farina, Ivano Notarnicola +1
This paper deals with a network of computing agents aiming to solve an online optimization problem in a distributed fashion, i.e., by means of local computation and communication,…
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…
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…
Distributed Submodular Minimization via Block-Wise Updates and Communications
Andrea Testa, Francesco Farina, Giuseppe Notarstefano
In this paper we deal with a network of computing agents with local processing and neighboring communication capabilities that aim at solving (without any central unit) a submodula…
Randomized Block Proximal Methods for Distributed Stochastic Big-Data Optimization
Francesco Farina, Giuseppe Notarstefano
In this paper we introduce a class of novel distributed algorithms for solving stochastic big-data convex optimization problems over directed graphs. In the addressed set-up, the d…
A Distributed Asynchronous Method of Multipliers for Constrained Nonconvex Optimization
Francesco Farina, Andrea Garulli, Antonio Giannitrapani +1
This paper presents a fully asynchronous and distributed approach for tackling optimization problems in which both the objective function and the constraints may be nonconvex. In t…
Distributed interpolatory algorithms for set membership estimation
Francesco Farina, Andrea Garulli, Antonio Giannitrapani
This work addresses the distributed estimation problem in a set membership framework. The agents of a network collect measurements which are affected by bounded errors, thus implyi…
Asynchronous Distributed Method of Multipliers for Constrained Nonconvex Optimization
Francesco Farina, Andrea Garulli, Antonio Giannitrapani +1
This paper addresses a class of constrained optimization problems over networks in which local cost functions and constraints can be nonconvex. We propose an asynchronous distribut…