Nicola Bastianello

According to our database, Nicola Bastianello authored at least 31 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A Stochastic Operator Framework for Optimization and Learning With Sub-Weibull Errors.

Nicola Bastianello, Liam Madden, Ruggero Carli, Emiliano Dall'Anese

IEEE Trans. Autom. Control., December, 2024

Internal Model-Based Online Optimization.

Nicola Bastianello, Ruggero Carli, Sandro Zampieri

IEEE Trans. Autom. Control., January, 2024

Hierarchical Federated ADMM.

Seyed Mohammad Azimi-Abarghouyi, Nicola Bastianello, Karl Henrik Johansson, Viktoria Fodor

CoRR, 2024

Learning and Verifying Maximal Taylor-Neural Lyapunov functions.

Matthieu Barreau, Nicola Bastianello

CoRR, 2024

Asynchronous Distributed Learning with Quantized Finite-Time Coordination.

Nicola Bastianello, Apostolos I. Rikos, Karl Henrik Johansson

CoRR, 2024

A survey on secure decentralized optimization and learning.

Changxin Liu, Nicola Bastianello, Wei Huo, Yang Shi, Karl Henrik Johansson

CoRR, 2024

Multi-Agent Optimization and Learning: A Non-Expansive Operators Perspective.

Nicola Bastianello, Luca Schenato, Ruggero Carli

CoRR, 2024

Enhancing Privacy in Federated Learning through Local Training.

Nicola Bastianello, Changxin Liu, Karl Henrik Johansson

CoRR, 2024

Energy Reduction in Cell-Free Massive MIMO through Fine-Grained Resource Management.

Özlem Tugfe Demir, Lianet Méndez-Monsanto, Nicola Bastianello, Emma Fitzgerald, Gilles Callebaut

Proceedings of the Joint European Conference on Networks and Communications & 6G Summit, 2024

Real-Time Anomaly Detection and Categorization for Satellite Reaction Wheels.

Alejandro Penacho Riveiros, Yu Xing, Nicola Bastianello, Karl Henrik Johansson

Proceedings of the European Control Conference, 2024

2023

Extrapolation-Based Prediction-Correction Methods for Time-varying Convex Optimization.

Nicola Bastianello, Ruggero Carli, Andrea Simonetto

Signal Process., 2023

A Control Theoretical Approach to Online Constrained Optimization.

Umberto Casti, Nicola Bastianello, Ruggero Carli, Sandro Zampieri

CoRR, 2023

Online Distributed Learning over Random Networks.

Nicola Bastianello, Diego Deplano, Mauro Franceschelli, Karl Henrik Johansson

CoRR, 2023

A Unified Approach to Solve the Dynamic Consensus on the Average, Maximum, and Median Values with Linear Convergence.

Diego Deplano, Nicola Bastianello, Mauro Franceschelli, Karl Henrik Johansson

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

Online Distributed Learning with Quantized Finite-Time Coordination.

Nicola Bastianello, Apostolos I. Rikos, Karl Henrik Johansson

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

2022

Feedback-Based Optimization With Sub-Weibull Gradient Errors and Intermittent Updates.

Ana M. Ospina, Nicola Bastianello, Emiliano Dall'Anese

IEEE Control. Syst. Lett., 2022

A novel bound on the convergence rate of ADMM for distributed optimization.

Nicola Bastianello, Luca Schenato, Ruggero Carli

Autom., 2022

OpReg-Boost: Learning to Accelerate Online Algorithms with Operator Regression.

Nicola Bastianello, Andrea Simonetto, Emiliano Dall'Anese

Proceedings of the Learning for Dynamics and Control Conference, 2022

2021

Asynchronous Distributed Optimization Over Lossy Networks via Relaxed ADMM: Stability and Linear Convergence.

Nicola Bastianello, Ruggero Carli, Luca Schenato, Marco Todescato

IEEE Trans. Autom. Control., 2021

Data-based Online Optimization of Networked Systems with Infrequent Feedback.

Ana M. Ospina, Nicola Bastianello, Emiliano Dall'Anese

CoRR, 2021

A Stochastic Operator Framework for Inexact Static and Online Optimization.

Nicola Bastianello, Liam Madden, Ruggero Carli, Emiliano Dall'Anese

CoRR, 2021

Distributed and Inexact Proximal Gradient Method for Online Convex Optimization.

Nicola Bastianello, Emiliano Dall'Anese

Proceedings of the 2021 European Control Conference, 2021

tvopt: A Python Framework for Time-Varying Optimization.

Nicola Bastianello

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

Prediction-Correction Splittings for Time-Varying Optimization With Intermittent Observations.

Nicola Bastianello, Andrea Simonetto, Ruggero Carli

IEEE Control. Syst. Lett., 2020

Primal and Dual Prediction-Correction Methods for Time-Varying Convex Optimization.

Nicola Bastianello, Andrea Simonetto, Ruggero Carli

CoRR, 2020

Distributed Prediction-Correction ADMM for Time-Varying Convex Optimization.

Nicola Bastianello, Andrea Simonetto, Ruggero Carli

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019

Prediction-correction for Nonsmooth Time-varying Optimization via Forward-backward Envelopes.

Nicola Bastianello, Andrea Simonetto, Ruggero Carli

Proceedings of the IEEE International Conference on Acoustics, 2019

Prediction-Correction Splittings for Nonsmooth Time-Varying Optimization.

Nicola Bastianello, Andrea Simonetto, Ruggero Carli

Proceedings of the 17th European Control Conference, 2019

2018

Distributed Optimization over Lossy Networks via Relaxed Peaceman-Rachford Splitting: a Robust ADMM Approach.

Nicola Bastianello, Marco Todescato, Ruggero Carli, Luca Schenato

Proceedings of the 16th European Control Conference, 2018

A Partition-Based Implementation of the Relaxed ADMM for Distributed Convex Optimization over Lossy Networks.

Nicola Bastianello, Ruggero Carli, Luca Schenato, Marco Todescato

Proceedings of the 57th IEEE Conference on Decision and Control, 2018