Nicola Bastianello

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 31

Top Topics

Gradient Method

Distributed Learning

Optimization Process

Convex Optimization

Top Venues

IEEE Control. Syst. Lett.

Publications

Nicola Bastianello, Ruggero Carli, Sandro Zampieri
Internal Model-Based Online Optimization. IEEE Trans. Autom. Control. 69 (1) (2024)
Nicola Bastianello, Luca Schenato, Ruggero Carli
Multi-Agent Optimization and Learning: A Non-Expansive Operators Perspective. CoRR (2024)
Özlem Tugfe Demir, Lianet Méndez-Monsanto, Nicola Bastianello, Emma Fitzgerald, Gilles Callebaut
Energy Reduction in Cell-Free Massive MIMO through Fine-Grained Resource Management. CoRR (2024)
Nicola Bastianello, Changxin Liu, Karl Henrik Johansson
Enhancing Privacy in Federated Learning through Local Training. CoRR (2024)
Alejandro Penacho Riveiros, Yu Xing, Nicola Bastianello, Karl H. Johansson
Real-Time Anomaly Detection and Categorization for Satellite Reaction Wheels. ECC (2024)
Özlem Tugfe Demir, Lianet Méndez-Monsanto, Nicola Bastianello, Emma Fitzgerald, Gilles Callebaut
Energy Reduction in Cell-Free Massive MIMO through Fine-Grained Resource Management. EuCNC/6G Summit (2024)
Nicola Bastianello, Ruggero Carli, Andrea Simonetto
Extrapolation-Based Prediction-Correction Methods for Time-varying Convex Optimization. Signal Process. 210 (2023)
Nicola Bastianello, Apostolos I. Rikos, Karl Henrik Johansson
Online Distributed Learning with Quantized Finite-Time Coordination. CoRR (2023)
Diego Deplano, Nicola Bastianello, Mauro Franceschelli, Karl Henrik Johansson
A Unified Approach to Solve the Dynamic Consensus on the Average, Maximum, and Median Values with Linear Convergence. CDC (2023)
Nicola Bastianello, Apostolos I. Rikos, Karl Henrik Johansson
Online Distributed Learning with Quantized Finite-Time Coordination. CDC (2023)
Guido Carnevale, Nicola Bastianello, Ruggero Carli, Giuseppe Notarstefano
Distributed Consensus Optimization via ADMM-Tracking Gradient. CDC (2023)
Umberto Casti, Nicola Bastianello, Ruggero Carli, Sandro Zampieri
A Control Theoretical Approach to Online Constrained Optimization. CoRR (2023)
Nicola Bastianello, Diego Deplano, Mauro Franceschelli, Karl Henrik Johansson
Online Distributed Learning over Random Networks. CoRR (2023)
Ana M. Ospina, Nicola Bastianello, Emiliano Dall'Anese
Feedback-Based Optimization With Sub-Weibull Gradient Errors and Intermittent Updates. IEEE Control. Syst. Lett. 6 (2022)
Nicola Bastianello, Ruggero Carli, Sandro Zampieri
Internal Model-Based Online Optimization. CoRR (2022)
Nicola Bastianello, Luca Schenato, Ruggero Carli
A novel bound on the convergence rate of ADMM for distributed optimization. Autom. 142 (2022)
Nicola Bastianello, Andrea Simonetto, Emiliano Dall'Anese
OpReg-Boost: Learning to Accelerate Online Algorithms with Operator Regression. L4DC (2022)
Nicola Bastianello
tvopt: A Python Framework for Time-Varying Optimization. CDC (2021)
Nicola Bastianello, Emiliano Dall'Anese
Distributed and Inexact Proximal Gradient Method for Online Convex Optimization. ECC (2021)
Nicola Bastianello, Andrea Simonetto, Emiliano Dall'Anese
OpReg-Boost: Learning to Accelerate Online Algorithms with Operator Regression. CoRR (2021)
Nicola Bastianello, Liam Madden, Ruggero Carli, Emiliano Dall'Anese
A Stochastic Operator Framework for Inexact Static and Online Optimization. CoRR (2021)
Ana M. Ospina, Nicola Bastianello, Emiliano Dall'Anese
Data-based Online Optimization of Networked Systems with Infrequent Feedback. CoRR (2021)
Nicola Bastianello, Ruggero Carli, Luca Schenato, Marco Todescato
Asynchronous Distributed Optimization Over Lossy Networks via Relaxed ADMM: Stability and Linear Convergence. IEEE Trans. Autom. Control. 66 (6) (2021)
Nicola Bastianello, Andrea Simonetto, Ruggero Carli
Primal and Dual Prediction-Correction Methods for Time-Varying Convex Optimization. CoRR (2020)
Nicola Bastianello, Andrea Simonetto, Ruggero Carli
Prediction-Correction Splittings for Time-Varying Optimization With Intermittent Observations. IEEE Control. Syst. Lett. 4 (2) (2020)
Nicola Bastianello, Andrea Simonetto, Ruggero Carli
Distributed Prediction-Correction ADMM for Time-Varying Convex Optimization. ACSSC (2020)
Nicola Bastianello
tvopt: A Python Framework for Time-Varying Optimization. CoRR (2020)
Nicola Bastianello, Andrea Simonetto, Ruggero Carli
Prediction-Correction Splittings for Nonsmooth Time-Varying Optimization. ECC (2019)
Nicola Bastianello, Andrea Simonetto, Ruggero Carli
Prediction-correction for Nonsmooth Time-varying Optimization via Forward-backward Envelopes. ICASSP (2019)
Nicola Bastianello, Marco Todescato, Ruggero Carli, Luca Schenato
Distributed Optimization over Lossy Networks via Relaxed Peaceman-Rachford Splitting: a Robust ADMM Approach. ECC (2018)
Nicola Bastianello, Ruggero Carli, Luca Schenato, Marco Todescato
A Partition-Based Implementation of the Relaxed ADMM for Distributed Convex Optimization over Lossy Networks. CDC (2018)