Guido Carnevale

According to our database, Guido Carnevale authored at least 43 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Safe Control of Feedback-Interconnected Systems via Singular Perturbations.

Stefano Di Gregorio, Guido Carnevale, Giuseppe Notarstefano

CoRR, April, 2026

2025

A Unifying System Theory Framework for Distributed Optimization and Games.

Guido Carnevale, Nicola Mimmo, Giuseppe Notarstefano

IEEE Trans. Autom. Control., November, 2025

Accelerated ADMM: Automated Parameter Tuning and Improved Linear Convergence.

Meisam Tavakoli, Fabian Jakob, Guido Carnevale, Giuseppe Notarstefano, Andrea Iannelli

CoRR, November, 2025

Nonlinear MPC for Feedback-Interconnected Systems: a Suboptimal and Reduced-Order Model Approach.

Stefano Di Gregorio, Guido Carnevale, Giuseppe Notarstefano

CoRR, November, 2025

ADMM-Tracking Gradient for Distributed Optimization Over Asynchronous and Unreliable Networks.

Guido Carnevale, Nicola Bastianello, Giuseppe Notarstefano, Ruggero Carli

IEEE Trans. Autom. Control., August, 2025

A Distributed Feedback-Based Framework for Nonlinear Aggregative Optimal Control.

Lorenzo Sforni, Guido Carnevale, Giuseppe Notarstefano

IEEE Trans. Autom. Control., June, 2025

Extremum Seeking Tracking for Derivative-Free Distributed Optimization.

Nicola Mimmo, Guido Carnevale, Andrea Testa, Giuseppe Notarstefano

IEEE Trans. Control. Netw. Syst., March, 2025

Data-Driven Distributed Optimization via Aggregative Tracking and Deep-Learning.

Riccardo Brumali, Guido Carnevale, Giuseppe Notarstefano

CoRR, March, 2025

Distributed Constraint-Coupled Optimization: Harnessing ADMM-consensus for robustness.

Messilem A. Mohamed, Guido Carnevale, Ruggero Carli

CoRR, February, 2025

On Sufficient Richness for Linear Time-Invariant Systems.

Marco Borghesi, Simone Baroncini, Guido Carnevale, Alessandro Bosso, Giuseppe Notarstefano

CoRR, February, 2025

A Tutorial on Distributed Optimization for Cooperative Robotics: From Setups and Algorithms to Toolboxes and Research Directions.

Andrea Testa, Guido Carnevale, Giuseppe Notarstefano

Proc. IEEE, January, 2025

Distributed learning and optimization of a multi-agent macroscopic probabilistic model.

Riccardo Brumali, Guido Carnevale, Giuseppe Notarstefano

Eur. J. Control, 2025

Modular Distributed Nonconvex Learning With Error Feedback.

Guido Carnevale, Nicola Bastianello

IEEE Control. Syst. Lett., 2025

Accelerating Model-Free Optimization via Averaging of Cost Samples.

Guido Carnevale, Giuseppe Notarstefano

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Data-Driven nonlinear optimal control via feedback-based extremum seeking.

Guido Carnevale, Giuseppe Notarstefano

Proceedings of the 64th IEEE Conference on Decision and Control, 2025

Almost Sure Convergence in Feedback Optimization via Stochastic Timescale Separation.

Guido Carnevale, Giuseppe Notarstefano

Proceedings of the 64th IEEE Conference on Decision and Control, 2025

A Feedback-Based Distributed Method for Multiscale Optimal Control of Multi-Agent Systems.

Riccardo Brumali, Guido Carnevale, Giuseppe Notarstefano

Proceedings of the 64th IEEE Conference on Decision and Control, 2025

2024

Tracking-Based Distributed Equilibrium Seeking for Aggregative Games.

Guido Carnevale, Filippo Fabiani, Filiberto Fele, Kostas Margellos, Giuseppe Notarstefano

IEEE Trans. Autom. Control., September, 2024

Timescale Separation for Discrete-Time Nonlinear Stochastic Systems.

Guido Carnevale, Giuseppe Notarstefano

IEEE Control. Syst. Lett., 2024

Data-Driven LQR with Finite-Time Experiments via Extremum-Seeking Policy Iteration.

Guido Carnevale, Nicola Mimmo, Giuseppe Notarstefano

CoRR, 2024

Multi-Robot Target Monitoring and Encirclement via Triggered Distributed Feedback Optimization.

Lorenzo Pichierri, Guido Carnevale, Lorenzo Sforni, Giuseppe Notarstefano

CoRR, 2024

Stability-Certified On-Policy Data-Driven LQR via Recursive Learning and Policy Gradient.

Lorenzo Sforni, Guido Carnevale, Ivano Notarnicola, Giuseppe Notarstefano

CoRR, 2024

Nonconvex distributed feedback optimization for aggregative cooperative robotics.

Guido Carnevale, Nicola Mimmo, Giuseppe Notarstefano

Autom., 2024

A deep learning approach for distributed aggregative optimization with users' feedback.

Riccardo Brumali, Guido Carnevale, Giuseppe Notarstefano

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Nonconvex Big-Data Optimization via System Theory: a Block-wise Incremental Gradient Method.

Guido Carnevale, Ivano Notarnicola, Giuseppe Notarstefano

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

Extremum-Seeking Policy Iteration for Data-Driven LQR.

Guido Carnevale, Nicola Mimmo, Giuseppe Notarstefano

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

Distributed equilibrium seeking in aggregative games: linear convergence under singular perturbations lens.

Guido Carnevale, Filippo Fabiani, Filiberto Fele, Kostas Margellos, Giuseppe Notarstefano

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

A System-theoretic Note on Model-Based Actor-Critic.

Simone Baroncini, Guido Carnevale, Bahman Gharesifard, Giuseppe Notarstefano

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

Distributed Feedback Optimization for Multi-Robot Target Encirclement and Patrolling.

Lorenzo Pichierri, Guido Carnevale, Giuseppe Notarstefano

Proceedings of the 20th IEEE International Conference on Automation Science and Engineering, 2024

Distributed ℓ0 Sparse Aggregative Optimization.

Alireza Olama, Guido Carnevale, Giuseppe Notarstefano, Eduardo Camponogara

Proceedings of the 20th IEEE International Conference on Automation Science and Engineering, 2024

A Distributed Algorithm for Coordination in Energy Communities.

Riccardo Brumali, Guido Carnevale, Ruggero Carli, Giuseppe Notarstefano

Proceedings of the 20th IEEE International Conference on Automation Science and Engineering, 2024

2023

GTAdam: Gradient Tracking With Adaptive Momentum for Distributed Online Optimization.

Guido Carnevale, Francesco Farina, Ivano Notarnicola, Giuseppe Notarstefano

IEEE Trans. Control. Netw. Syst., September, 2023

Distributed Online Aggregative Optimization for Dynamic Multirobot Coordination.

Guido Carnevale, Andrea Camisa, Giuseppe Notarstefano

IEEE Trans. Autom. Control., June, 2023

Distributed optimization and games over networks: a system theoretical perspective.

Guido Carnevale

PhD thesis, 2023

Nonconvex Distributed Optimization via Lasalle and Singular Perturbations.

Guido Carnevale, Giuseppe Notarstefano

IEEE Control. Syst. Lett., 2023

Triggered Gradient Tracking for asynchronous distributed optimization.

Guido Carnevale, Ivano Notarnicola, Lorenzo Marconi, Giuseppe Notarstefano

Autom., 2023

A Distributed Online Optimization Strategy for Cooperative Robotic Surveillance.

Lorenzo Pichierri, Guido Carnevale, Lorenzo Sforni, Andrea Testa, Giuseppe Notarstefano

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

A Tracking Augmented Lagrangian Method for ℓ0 Sparse Consensus Optimization.

Alireza Olama, Guido Carnevale, Giuseppe Notarstefano, Eduardo Camponogara

Proceedings of the 9th International Conference on Control, 2023

On-Policy Data-Driven Linear Quadratic Regulator via Combined Policy Iteration and Recursive Least Squares.

Lorenzo Sforni, Guido Carnevale, Ivano Notarnicola, Giuseppe Notarstefano

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Distributed Consensus Optimization via ADMM-Tracking Gradient.

Guido Carnevale, Nicola Bastianello, Ruggero Carli, Giuseppe Notarstefano

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

A Learning-based Distributed Algorithm for Personalized Aggregative Optimization.

Guido Carnevale, Giuseppe Notarstefano

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021

Distributed Online Aggregative Optimization for Dynamic Multi-robot Coordination.

Guido Carnevale, Andrea Camisa, Giuseppe Notarstefano

CoRR, 2021

2020

Distributed Online Optimization via Gradient Tracking with Adaptive Momentum.

Guido Carnevale, Francesco Farina, Ivano Notarnicola, Giuseppe Notarstefano

CoRR, 2020