101 citations · 174 across the 22 of their papers we have counts for
11 papers · 1 filter
Stability-Certified On-Policy Data-Driven LQR via Recursive Learning and Policy Gradient
Lorenzo Sforni, Guido Carnevale, Ivano Notarnicola +1
In this paper, we investigate a data-driven framework to solve Linear Quadratic Regulator (LQR) problems when the dynamics is unknown, with the additional challenge of providing st…
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…
A System Theoretical Perspective to Gradient-Tracking Algorithms for Distributed Quadratic Optimization
Michelangelo Bin, Ivano Notarnicola, Lorenzo Marconi +1
In this paper we consider a recently developed distributed optimization algorithm based on gradient tracking. We propose a system theory framework to analyze its structural propert…
Distributed Optimization for Smart Cyber-Physical Networks
Giuseppe Notarstefano, Ivano Notarnicola, Andrea Camisa
The presence of embedded electronics and communication capabilities as well as sensing and control in smart devices has given rise to the novel concept of cyber-physical networks,…
Distributed Submodular Minimization over Networks: a Greedy Column Generation Approach
Andrea Testa, Ivano Notarnicola, Giuseppe Notarstefano
Submodular optimization is a special class of combinatorial optimization arising in several machine learning problems, but also in cooperative control of complex systems. In this p…
A Primal Decomposition Method with Suboptimality Bounds for Distributed Mixed-Integer Linear Programming
Andrea Camisa, Ivano Notarnicola, Giuseppe Notarstefano
In this paper we deal with a network of agents seeking to solve in a distributed way Mixed-Integer Linear Programs (MILPs) with a coupling constraint (modeling a limited shared res…
Distributed Partitioned Big-Data Optimization via Asynchronous Dual Decomposition
Ivano Notarnicola, Ruggero Carli, Giuseppe Notarstefano
In this paper we consider a novel partitioned framework for distributed optimization in peer-to-peer networks. In several important applications the agents of a network have to sol…
A Duality-Based Approach for Distributed Optimization with Coupling Constraints
Ivano Notarnicola, Giuseppe Notarstefano
In this paper we consider a distributed optimization scenario in which a set of agents has to solve a convex optimization problem with separable cost function, local constraint set…
Constraint Coupled Distributed Optimization: a Relaxation and Duality Approach
Ivano Notarnicola, Giuseppe Notarstefano
In this paper we consider a general, challenging distributed optimization set-up arising in several important network control applications. Agents of a network want to minimize the…
Final-State Constrained Optimal Control via a Projection Operator Approach
Ivano Notarnicola, Florian A. Bayer, Giuseppe Notarstefano +1
In this paper we develop a numerical method to solve nonlinear optimal control problems with final-state constraints. Specifically, we extend the PRojection Operator based Netwon's…
Asynchronous Distributed Optimization via Randomized Dual Proximal Gradient
Ivano Notarnicola, Giuseppe Notarstefano
In this paper we consider distributed optimization problems in which the cost function is separable, i.e., a sum of possibly non-smooth functions all sharing a common variable, and…