| Walking ahead: The headed social force model F Farina, D Fontanelli, A Garulli, A Giannitrapani, D Prattichizzo PloS one 12 (1), e0169734, 2017 | 174 | 2017 |
| Upper body pose estimation using wearable inertial sensors and multiplicative kalman filter TL Baldi, F Farina, A Garulli, A Giannitrapani, D Prattichizzo IEEE Sensors Journal 20 (1), 492-500, 2019 | 56 | 2019 |
| Disropt: a python framework for distributed optimization F Farina, A Camisa, A Testa, I Notarnicola, G Notarstefano IFAC-PapersOnLine 53 (2), 2666-2671, 2020 | 47 | 2020 |
| GTAdam: Gradient tracking with adaptive momentum for distributed online optimization G Carnevale, F Farina, I Notarnicola, G Notarstefano IEEE Transactions on Control of Network Systems 10 (3), 1436-1448, 2022 | 34* | 2022 |
| A distributed asynchronous method of multipliers for constrained nonconvex optimization F Farina, A Garulli, A Giannitrapani, G Notarstefano Automatica 103, 243-253, 2019 | 34 | 2019 |
| Distributed Constraint-Coupled Optimization via Primal Decomposition over Random Time-Varying Graphs A Camisa, F Farina, I Notarnicola, G Notarstefano Automatica 131 (4), 2021 | 21 | 2021 |
| Distributed personalized gradient tracking with convex parametric models I Notarnicola, A Simonetto, F Farina, G Notarstefano IEEE Transactions on Automatic Control 68 (1), 588-595, 2022 | 20 | 2022 |
| When Helbing meets Laumond: the headed social force model F Farina, D Fontanelli, A Garulli, A Giannitrapani, D Prattichizzo 2016 IEEE 55th Conference on Decision and Control (CDC), 3548-3553, 2016 | 18 | 2016 |
| Randomized Block Proximal Methods for Distributed Stochastic Big-Data Optimization F Farina, G Notarstefano IEEE Transactions on Automatic Control, 2020 | 11 | 2020 |
| Minimum switching thruster control for spacecraft precision pointing M Leomanni, A Garulli, A Giannitrapani, F Farina, F Scortecci IEEE Transactions on Aerospace and Electronic Systems 53 (2), 683-697, 2017 | 10 | 2017 |
| Distributed constraint-coupled optimization over random time-varying graphs via primal decomposition and block subgradient approaches A Camisa, F Farina, I Notarnicola, G Notarstefano 2019 IEEE 58th Conference on Decision and Control (CDC), 6374-6379, 2019 | 9 | 2019 |
| Distributed interpolatory algorithms for set membership estimation F Farina, A Garulli, A Giannitrapani IEEE Transactions on Automatic Control, 2018 | 9 | 2018 |
| Asynchronous distributed learning from constraints F Farina, S Melacci, A Garulli, A Giannitrapani IEEE transactions on neural networks and learning systems 31 (10), 4367-4373, 2019 | 7 | 2019 |
| A randomized block subgradient approach to distributed big data optimization F Farina, G Notarstefano 2019 IEEE 58th Conference on Decision and Control (CDC), 6362-6367, 2019 | 5 | 2019 |
| An interpolatory algorithm for distributed set membership estimation in asynchronous networks F Farina, A Garulli, A Giannitrapani IEEE Transactions on Automatic Control 67 (10), 5464-5470, 2021 | 3 | 2021 |
| Data efficiency in graph networks through equivariance F Farina, E Slade ICML 2021 Workshop on Subset Selection in Machine Learning: From Theory to …, 2021 | 3 | 2021 |
| Multi-agent active learning for distributed black-box optimization L Cannelli, M Zhu, F Farina, A Bemporad, D Piga IEEE Control Systems Letters 7, 1488-1493, 2023 | 2 | 2023 |
| Symmetry-driven graph neural networks F Farina, E Slade arXiv preprint arXiv:2105.14058, 2021 | 2 | 2021 |
| Distributed set membership estimation with time-varying graph topology F Farina, A Garulli, A Giannitrapani 2019 IEEE 58th Conference on Decision and Control (CDC), 4121-4126, 2019 | 2 | 2019 |
| Collective Learning F Farina arXiv preprint arXiv:1912.02580, 2019 | 2 | 2019 |
Antonello GiannitrapaniAssociate Professor, University of Siena確認したメール アドレス: dii.unisi.it