Asynchronous distributed optimization over lossy networks via relaxed ADMM: Stability and linear convergence N Bastianello, R Carli, L Schenato, M Todescato IEEE Transactions on Automatic Control 66 (6), 2620-2635, 2020 | 77 | 2020 |
Distributed and inexact proximal gradient method for online convex optimization N Bastianello, E Dall’Anese 2021 European Control Conference (ECC), 2432-2437, 2021 | 35 | 2021 |
Distributed optimization over lossy networks via relaxed peaceman-rachford splitting: a robust admm approach N Bastianello, M Todescato, R Carli, L Schenato 2018 European Control Conference (ECC), 477-482, 2018 | 25 | 2018 |
Primal and dual prediction-correction methods for time-varying convex optimization N Bastianello, A Simonetto, R Carli arXiv preprint arXiv:2004.11709, 2020 | 17 | 2020 |
A partition-based implementation of the relaxed ADMM for distributed convex optimization over lossy networks N Bastianello, R Carli, L Schenato, M Todescato 2018 IEEE Conference on Decision and Control (CDC), 3379-3384, 2018 | 12 | 2018 |
tvopt: A python framework for time-varying optimization N Bastianello 2021 60th IEEE Conference on Decision and Control (CDC), 227-232, 2021 | 11 | 2021 |
Distributed prediction-correction admm for time-varying convex optimization N Bastianello, A Simonetto, R Carli 2020 54th Asilomar Conference on Signals, Systems, and Computers, 47-52, 2020 | 11 | 2020 |
Relaxed hybrid consensus ADMM for distributed convex optimisation with coupling constraints A Olama, N Bastianello, PRC Mendes, E Camponogara IET Control Theory & Applications 13 (17), 2828-2837, 2019 | 11 | 2019 |
A stochastic operator framework for inexact static and online optimization N Bastianello, L Madden, R Carli, E Dall’Anese arXiv preprint arXiv:2105.09884, 2021 | 10 | 2021 |
Prediction-correction splittings for nonsmooth time-varying optimization N Bastianello, A Simonetto, R Carli 2019 18th European Control Conference (ECC), 1963-1968, 2019 | 9 | 2019 |
Feedback-based optimization with sub-weibull gradient errors and intermittent updates AM Ospina, N Bastianello, E Dall’Anese IEEE Control Systems Letters 6, 2521-2526, 2022 | 8 | 2022 |
Internal Model-Based Online Optimization N Bastianello, R Carli, S Zampieri IEEE Transactions on Automatic Control, 2023 | 7 | 2023 |
Extrapolation-based prediction-correction methods for time-varying convex optimization N Bastianello, R Carli, A Simonetto Signal Processing 210, 109089, 2023 | 6 | 2023 |
Online distributed learning over random networks N Bastianello, D Deplano, M Franceschelli, KH Johansson arXiv preprint arXiv:2309.00520, 2023 | 5 | 2023 |
A novel bound on the convergence rate of ADMM for distributed optimization N Bastianello, L Schenato, R Carli Automatica 142, 110403, 2022 | 5 | 2022 |
A stochastic operator framework for optimization and learning with sub-weibull errors N Bastianello, L Madden, R Carli, E Dall'Anese IEEE Transactions on Automatic Control, 2024 | 4 | 2024 |
Distributed consensus optimization via ADMM-tracking gradient G Carnevale, N Bastianello, R Carli, G Notarstefano 2023 62nd IEEE Conference on Decision and Control (CDC), 290-295, 2023 | 4 | 2023 |
A unified approach to solve the dynamic consensus on the average, maximum, and median values with linear convergence D Deplano, N Bastianello, M Franceschelli, KH Johansson 2023 62nd IEEE Conference on Decision and Control (CDC), 6442-6448, 2023 | 4 | 2023 |
ADMM-tracking gradient for distributed optimization over asynchronous and unreliable networks G Carnevale, N Bastianello, G Notarstefano, R Carli arXiv preprint arXiv:2309.14142, 2023 | 4 | 2023 |
Admm for dynamic average consensus over imperfect networks N Bastianello, R Carli IFAC-PapersOnLine 55 (13), 228-233, 2022 | 4 | 2022 |