collaborators

5 papers

eess.SY2025

Non-Euclidean Enriched Contraction Theory for Monotone Operators and Monotone Dynamical Systems

Diego Deplano, Sergio Grammatico, Mauro Franceschelli

We adopt an operator-theoretic perspective to analyze a class of nonlinear fixed-point iterations and discrete-time dynamical systems. Specifically, we study the Krasnoselskij iter…

math.OC2025

Optimization and Learning in Open Multi-Agent Systems

Diego Deplano, Nicola Bastianello, Mauro Franceschelli +1

Modern artificial intelligence relies on networks of agents that collect data, process information, and exchange it with neighbors to collaboratively solve optimization and learnin…

eess.SY2024

Algebraic Connectivity Control and Maintenance in Multi-Agent Networks under Attack

Wenjie Zhao, Diego Deplano, Zhiwu Li +2

This paper studies the problem of increasing the connectivity of an ad-hoc peer-to-peer network subject to cyber-attacks targeting the agents in the network. The adopted strategy i…

math.OC2024

Robust Online Learning over Networks

Nicola Bastianello, Diego Deplano, Mauro Franceschelli +1

The recent deployment of multi-agent networks has enabled the distributed solution of learning problems, where agents cooperate to train a global model without sharing their local,…

math.OC2024

Accelerated Alternating Direction Method of Multipliers Gradient Tracking for Distributed Optimization

Eduardo Sebastián, Mauro Franceschelli, Andrea Gasparri +2

This paper presents a novel accelerated distributed algorithm for unconstrained consensus optimization over static undirected networks. The proposed algorithm combines the benefits…