54 citations · 144 across the 14 of their papers we have counts for
14 papers
Venture Capital Portfolio Construction and the Main Factors Impacting the Optimal Strategy
Francesco Farina, Mike Arpaia, Harpal Khing +1
The optimal portfolio size for a venture capital (VC) fund is a topic often debated, but there is no consensus on the best strategy. This is because it is a function of many factor…
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…
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,…
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…
Upper Body Pose Estimation Using Wearable Inertial Sensors and Multiplicative Kalman Filter
Tommaso Lisini Baldi, Francesco Farina, Andrea Garulli +2
Estimating the limbs pose in a wearable way may benefit multiple areas such as rehabilitation, teleoperation, human-robot interaction, gaming, and many more. Several solutions are…
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…