Research

My research interests span a number of topics, including optimization theory, distributed (multi-agent) optimization, geometric deep learning, causal discovery, uncertainty estimation, control theory and finance.

Some of works appeared in Automatica (Elsevier), IEEE Transactions on Automatic Control, IEEE Transactions on Neural Networks and Learning Systems, International Conference on Machine Learning (ICML), IEEE Control and Decision Conference (CDC), and Plos ONE.

Some others remained just preprints...

Below you can find all my publications or you can check out my Google Scholar.

Showing 26 papers

Publications by year

2023

Multi-agent active learning for distributed black-box optimization

Cannelli, L., Zhu, M., Farina, F., Bemporad, A., Piga, D.

IEEE Control Systems Letters (2023)

Distributed Optimization
Multi-Agent Systems

Venture Capital Portfolio Construction and the Main Factors Impacting the Optimal Strategy

Farina, F., Arpaia, M., Khing, H., Vetterle, J.

arXiv preprint arXiv:2303.11013 (2023)

Finance

2022

Distributed personalized gradient tracking with convex parametric models

Notarnicola, I., Simonetto, A., Farina, F., Notarstefano, G.

IEEE Transactions on Automatic Control, 68(1), 588-595 (2022)

Distributed Optimization
Control Theory

GTAdam: Gradient tracking with adaptive momentum for distributed online optimization

Carnevale, G., Farina, F., Notarnicola, I., Notarstefano, G.

IEEE Transactions on Control of Network Systems, 10(3), 1436-1448 (2022)

Distributed Optimization
Machine Learning

2021

An Interpolatory Algorithm for Distributed Set Membership Estimation in Asynchronous Networks

Farina, F., Garulli, A., Giannitrapani, A.

IEEE Transactions on Automatic Control, 67(10), 5464-5470 (2021)

Multi-Agent Systems
Control Theory

Distributed constraint-coupled optimization via primal decomposition over random time-varying graphs

Camisa, A., Farina, F., Notarnicola, I., Notarstefano, G.

Automatica, 131, 109739 (2021)

Distributed Optimization
Control Theory

Intrinsic uncertainties and where to find them

Farina, F., et al.

ICML 2021 workshop on Uncertainty and Robustness in Deep Learning (2021)

Machine Learning

Data efficiency in graph networks via equivariance

Farina, F., et al.

ICML 2021 Workshop on Subset Selection in Machine Learning: From Theory to Practice (2021)

Graph Neural Networks
Machine Learning

Symmetry-driven graph neural networks

Farina, F., Slade, E.

arXiv preprint arXiv:2105.14058 (2021)

Graph Neural Networks
Machine Learning

Beyond permutation equivariance in graph networks

Slade, E., Farina, F.

arXiv preprint arXiv:2103.14066 (2021)

Graph Neural Networks
Machine Learning

2020

Randomized Block Proximal Methods for Distributed Stochastic Big-Data Optimization

Farina, F., Notarstefano, G.

IEEE Transactions on Automatic Control (2020)

Distributed Optimization
Machine Learning

On the Linear Convergence Rate of the Distributed Block Proximal Method

Farina, F., Notarstefano, G.

IEEE Control Systems Letters (2020)

Distributed Optimization

Upper Body Pose Estimation Using Wearable Inertial Sensors and Multiplicative Kalman Filter

Lisini Baldi, T., Farina, F., Garulli, A., Giannitrapani, A., Prattichizzo, D.

IEEE Sensors Journal, 20(1), 492-500 (2020)

Control Theory

DISROPT: a Python Framework for Distributed Optimization

Farina, F., Camisa, A., Testa, A., Notarnicola, I., Notarstefano, G.

21st IFAC World Congress (2020)

Distributed Optimization

Distributed Submodular Minimization via Block-Wise Updates and Communications

Farina, F., Testa, A., Notarstefano, G.

21st IFAC World Congress (2020)

Distributed Optimization

2019

Asynchronous Distributed Learning From Constraints

Farina, F., Melacci, S., Garulli, A., Giannitrapani, A.

IEEE Transactions on Neural Networks and Learning Systems (2019)

Distributed Optimization
Machine Learning

Distributed interpolatory algorithms for set membership estimation

Farina, F., Garulli, A., Giannitrapani, A.

IEEE Transactions on Automatic Control, 64(9), 3817-3822 (2019)

Control Theory
Multi-Agent Systems

A distributed asynchronous method of multipliers for constrained nonconvex optimization

Farina, F., Garulli, A., Giannitrapani, A., Notarstefano, G.

Automatica, 103, 243-253 (2019)

Distributed Optimization
Control Theory

A Randomized Block Subgradient Approach to Distributed Big Data Optimization

Farina, F., Notarstefano, G.

2019 IEEE 58th Conference on Decision and Control (CDC) (2019)

Distributed Optimization
Machine Learning

Distributed set membership estimation with time-varying graph topology

Farina, F., Garulli, A., Giannitrapani, A.

2019 IEEE 58th Conference on Decision and Control (CDC) (2019)

Control Theory
Multi-Agent Systems

Distributed Constraint-Coupled Optimization over Random Time-Varying Graphs via Primal Decomposition and Block Subgradient Approaches

Camisa, A., Farina, F., Notarnicola, I., Notarstefano, G.

2019 IEEE 58th Conference on Decision and Control (CDC) (2019)

Distributed Optimization

Collective Learning

Farina, F.

arXiv:1912.02580 (2019)

Machine Learning
Multi-Agent Systems

2018

Asynchronous Distributed Method of Multipliers for Constrained Nonconvex optimization

Farina, F., Garulli, A., Giannitrapani, A., Notarstefano, G.

2018 European Control Conference (ECC) (2018)

Distributed Optimization
Control Theory

2017

Minimum Switching Thruster Control for Spacecraft Precision Pointing

Leomanni, M., Garulli, A., Giannitrapani, A., Farina, F., Scortecci, F.

IEEE Transactions on Aerospace and Electronic Systems, 53(2), 683-697 (2017)

Control Theory

Walking Ahead: The Headed Social Force Model

Farina, F., Fontanelli, D., Garulli, A., Giannitrapani, A., Prattichizzo, D.

PLOS ONE, 12(1), 1-23 (2017)

Multi-Agent Systems
Control Theory

2016

When Helbing meets Laumond: The Headed Social Force Model

Farina, F., Fontanelli, D., Garulli, A., Giannitrapani, A., Prattichizzo, D.

2016 IEEE 55th Conference on Decision and Control (CDC) (2016)

Multi-Agent Systems